├── .gitattributes
├── .github
├── ISSUE_TEMPLATE
│ ├── bug_report.yml
│ └── feature_request.yml
└── workflows
│ ├── build-with-all-capacity.yml
│ ├── build-with-audio-assistant.yml
│ ├── build-with-chatglm.yml
│ ├── build-with-latex-arm.yml
│ ├── build-with-latex.yml
│ ├── build-without-local-llms.yml
│ ├── conda-pack-windows.yml
│ └── stale.yml
├── .gitignore
├── Dockerfile
├── LICENSE
├── README.md
├── check_proxy.py
├── config.py
├── core_functional.py
├── crazy_functional.py
├── crazy_functions
├── Conversation_To_File.py
├── Image_Generate.py
├── Image_Generate_Wrap.py
├── Internet_GPT.py
├── Internet_GPT_Wrap.py
├── Latex_Function.py
├── Latex_Function_Wrap.py
├── Latex_Project_Polish.py
├── Latex_Project_Translate_Legacy.py
├── Markdown_Translate.py
├── PDF_Translate.py
├── PDF_Translate_Wrap.py
├── Rag_Interface.py
├── Social_Helper.py
├── SourceCode_Analyse.py
├── SourceCode_Comment.py
├── SourceCode_Comment_Wrap.py
├── VideoResource_GPT.py
├── __init__.py
├── agent_fns
│ ├── auto_agent.py
│ ├── echo_agent.py
│ ├── general.py
│ ├── persistent.py
│ ├── pipe.py
│ ├── python_comment_agent.py
│ ├── python_comment_compare.html
│ └── watchdog.py
├── ast_fns
│ └── comment_remove.py
├── crazy_utils.py
├── diagram_fns
│ └── file_tree.py
├── doc_fns
│ ├── AI_review_doc.py
│ ├── __init__.py
│ ├── batch_file_query_doc.py
│ ├── content_folder.py
│ ├── conversation_doc
│ │ ├── excel_doc.py
│ │ ├── html_doc.py
│ │ ├── markdown_doc.py
│ │ ├── pdf_doc.py
│ │ ├── txt_doc.py
│ │ ├── word2pdf.py
│ │ └── word_doc.py
│ └── read_fns
│ │ ├── __init__.py
│ │ ├── docx_reader.py
│ │ ├── excel_reader.py
│ │ ├── markitdown
│ │ └── markdown_reader.py
│ │ ├── unstructured_all
│ │ ├── __init__.py
│ │ ├── paper_metadata_extractor.py
│ │ ├── paper_structure_extractor.py
│ │ ├── unstructured_md.py
│ │ └── unstructured_reader.py
│ │ └── web_reader.py
├── game_fns
│ ├── game_ascii_art.py
│ ├── game_interactive_story.py
│ └── game_utils.py
├── gen_fns
│ └── gen_fns_shared.py
├── ipc_fns
│ └── mp.py
├── json_fns
│ ├── pydantic_io.py
│ └── select_tool.py
├── latex_fns
│ ├── latex_actions.py
│ ├── latex_pickle_io.py
│ └── latex_toolbox.py
├── live_audio
│ ├── aliyunASR.py
│ └── audio_io.py
├── media_fns
│ └── get_media.py
├── multi_stage
│ └── multi_stage_utils.py
├── pdf_fns
│ ├── breakdown_txt.py
│ ├── parse_pdf.py
│ ├── parse_pdf_grobid.py
│ ├── parse_pdf_legacy.py
│ ├── parse_pdf_via_doc2x.py
│ ├── parse_word.py
│ ├── report_gen_html.py
│ ├── report_template.html
│ └── report_template_v2.html
├── plugin_template
│ └── plugin_class_template.py
├── prompts
│ └── internet.py
├── rag_fns
│ ├── llama_index_worker.py
│ ├── milvus_worker.py
│ ├── rag_file_support.py
│ └── vector_store_index.py
├── vector_fns
│ ├── __init__.py
│ ├── general_file_loader.py
│ └── vector_database.py
├── vt_fns
│ ├── vt_call_plugin.py
│ ├── vt_modify_config.py
│ └── vt_state.py
├── word_dfa
│ └── dfa_algo.py
├── 下载arxiv论文翻译摘要.py
├── 互动小游戏.py
├── 交互功能函数模板.py
├── 函数动态生成.py
├── 命令行助手.py
├── 多智能体.py
├── 总结word文档.py
├── 总结音视频.py
├── 批量总结PDF文档.py
├── 批量总结PDF文档pdfminer.py
├── 批量翻译PDF文档_NOUGAT.py
├── 数学动画生成manim.py
├── 理解PDF文档内容.py
├── 生成函数注释.py
├── 生成多种Mermaid图表.py
├── 知识库问答.py
├── 联网的ChatGPT.py
├── 联网的ChatGPT_bing版.py
├── 虚空终端.py
├── 解析JupyterNotebook.py
├── 询问多个大语言模型.py
├── 语音助手.py
├── 读文章写摘要.py
├── 谷歌检索小助手.py
├── 辅助功能.py
└── 高级功能函数模板.py
├── docker-compose.yml
├── docs
├── Dockerfile+ChatGLM
├── Dockerfile+NoLocal+Latex
├── GithubAction+AllCapacity
├── GithubAction+ChatGLM+Moss
├── GithubAction+JittorLLMs
├── GithubAction+NoLocal
├── GithubAction+NoLocal+AudioAssistant
├── GithubAction+NoLocal+Latex
├── GithubAction+NoLocal+Vectordb
├── README.Arabic.md
├── README.English.md
├── README.French.md
├── README.German.md
├── README.Italian.md
├── README.Japanese.md
├── README.Korean.md
├── README.Portuguese.md
├── README.Russian.md
├── WindowsRun.bat
├── WithFastapi.md
├── demo.jpg
├── demo2.jpg
├── logo.png
├── plugin_with_secondary_menu.md
├── self_analysis.md
├── translate_english.json
├── translate_japanese.json
├── translate_std.json
├── translate_traditionalchinese.json
├── use_audio.md
├── use_azure.md
├── use_tts.md
└── use_vllm.md
├── main.py
├── multi_language.py
├── request_llms
├── README.md
├── bridge_all.py
├── bridge_chatglm.py
├── bridge_chatglm3.py
├── bridge_chatglm4.py
├── bridge_chatglmft.py
├── bridge_chatglmonnx.py
├── bridge_chatgpt.py
├── bridge_chatgpt_vision.py
├── bridge_claude.py
├── bridge_cohere.py
├── bridge_deepseekcoder.py
├── bridge_google_gemini.py
├── bridge_internlm.py
├── bridge_jittorllms_llama.py
├── bridge_jittorllms_pangualpha.py
├── bridge_jittorllms_rwkv.py
├── bridge_llama2.py
├── bridge_moonshot.py
├── bridge_moss.py
├── bridge_newbingfree.py
├── bridge_ollama.py
├── bridge_openrouter.py
├── bridge_qianfan.py
├── bridge_qwen.py
├── bridge_qwen_local.py
├── bridge_skylark2.py
├── bridge_spark.py
├── bridge_stackclaude.py
├── bridge_taichu.py
├── bridge_tgui.py
├── bridge_zhipu.py
├── chatglmoonx.py
├── com_google.py
├── com_qwenapi.py
├── com_skylark2api.py
├── com_sparkapi.py
├── com_taichu.py
├── com_zhipuglm.py
├── edge_gpt_free.py
├── embed_models
│ ├── bridge_all_embed.py
│ └── openai_embed.py
├── key_manager.py
├── local_llm_class.py
├── oai_std_model_template.py
├── queued_pipe.py
├── requirements_chatglm.txt
├── requirements_chatglm4.txt
├── requirements_chatglm_onnx.txt
├── requirements_jittorllms.txt
├── requirements_moss.txt
├── requirements_newbing.txt
├── requirements_qwen.txt
├── requirements_qwen_local.txt
└── requirements_slackclaude.txt
├── requirements.txt
├── shared_utils
├── advanced_markdown_format.py
├── char_visual_effect.py
├── colorful.py
├── config_loader.py
├── connect_void_terminal.py
├── context_clip_policy.py
├── cookie_manager.py
├── docker_as_service_api.py
├── fastapi_server.py
├── handle_upload.py
├── key_pattern_manager.py
├── logging.py
├── map_names.py
└── text_mask.py
├── tests
├── __init__.py
├── init_test.py
├── test_anim_gen.py
├── test_bilibili_down.py
├── test_doc2x.py
├── test_embed.py
├── test_key_pattern_manager.py
├── test_latex_auto_correct.py
├── test_llms.py
├── test_markdown.py
├── test_markdown_format.py
├── test_media.py
├── test_plugins.py
├── test_python_auto_docstring.py
├── test_rag.py
├── test_safe_pickle.py
├── test_save_chat_to_html.py
├── test_searxng.py
├── test_social_helper.py
├── test_tts.py
├── test_utils.py
└── test_vector_plugins.py
├── themes
├── base64.mjs
├── common.css
├── common.js
├── common.py
├── contrast.css
├── contrast.py
├── cookies.py
├── default.css
├── default.py
├── gradios.py
├── green.css
├── green.js
├── green.py
├── gui_advanced_plugin_class.py
├── gui_floating_menu.py
├── gui_toolbar.py
├── init.js
├── svg
│ ├── arxiv.svg
│ ├── box.svg
│ ├── brain.svg
│ ├── check.svg
│ ├── conf.svg
│ ├── default.svg
│ ├── doc.svg
│ ├── img.svg
│ ├── location.svg
│ ├── mm.svg
│ ├── polish.svg
│ ├── tts.svg
│ └── vt.svg
├── theme.js
├── theme.py
├── tts.js
├── waifu_plugin
│ ├── autoload.js
│ ├── flat-ui-icons-regular.eot
│ ├── flat-ui-icons-regular.svg
│ ├── flat-ui-icons-regular.ttf
│ ├── flat-ui-icons-regular.woff
│ ├── jquery-ui.min.js
│ ├── jquery.min.js
│ ├── live2d.js
│ ├── source
│ ├── waifu-tips.js
│ ├── waifu-tips.json
│ └── waifu.css
└── welcome.js
├── toolbox.py
└── version
/.gitattributes:
--------------------------------------------------------------------------------
1 | *.h linguist-detectable=false
2 | *.cpp linguist-detectable=false
3 | *.tex linguist-detectable=false
4 | *.cs linguist-detectable=false
5 | *.tps linguist-detectable=false
6 |
--------------------------------------------------------------------------------
/.github/ISSUE_TEMPLATE/bug_report.yml:
--------------------------------------------------------------------------------
1 | name: Report Bug | 报告BUG
2 | description: "Report bug"
3 | title: "[Bug]: "
4 | labels: []
5 | body:
6 | - type: dropdown
7 | id: download
8 | attributes:
9 | label: Installation Method | 安装方法与平台
10 | options:
11 | - Please choose | 请选择
12 | - Pip Install (I ignored requirements.txt)
13 | - Pip Install (I used latest requirements.txt)
14 | - OneKeyInstall (一键安装脚本-windows)
15 | - OneKeyInstall (一键安装脚本-mac)
16 | - Anaconda (I ignored requirements.txt)
17 | - Anaconda (I used latest requirements.txt)
18 | - Docker（Windows/Mac）
19 | - Docker（Linux）
20 | - Docker-Compose（Windows/Mac）
21 | - Docker-Compose（Linux）
22 | - Huggingface
23 | - Others (Please Describe)
24 | validations:
25 | required: true
26 |
27 | - type: dropdown
28 | id: version
29 | attributes:
30 | label: Version | 版本
31 | options:
32 | - Please choose | 请选择
33 | - Latest | 最新版
34 | - Others | 非最新版
35 | validations:
36 | required: true
37 |
38 | - type: dropdown
39 | id: os
40 | attributes:
41 | label: OS | 操作系统
42 | options:
43 | - Please choose | 请选择
44 | - Windows
45 | - Mac
46 | - Linux
47 | - Docker
48 | validations:
49 | required: true
50 |
51 | - type: textarea
52 | id: describe
53 | attributes:
54 | label: Describe the bug | 简述
55 | description: Describe the bug | 简述
56 | validations:
57 | required: true
58 |
59 | - type: textarea
60 | id: screenshot
61 | attributes:
62 | label: Screen Shot | 有帮助的截图
63 | description: Screen Shot | 有帮助的截图
64 | validations:
65 | required: true
66 |
67 | - type: textarea
68 | id: traceback
69 | attributes:
70 | label: Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
71 | description: Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
72 |
--------------------------------------------------------------------------------
/.github/ISSUE_TEMPLATE/feature_request.yml:
--------------------------------------------------------------------------------
1 | name: Feature Request | 功能请求
2 | description: "Feature Request"
3 | title: "[Feature]: "
4 | labels: []
5 | body:
6 | - type: dropdown
7 | id: download
8 | attributes:
9 | label: Class | 类型
10 | options:
11 | - Please choose | 请选择
12 | - 其他
13 | - 函数插件
14 | - 大语言模型
15 | - 程序主体
16 | validations:
17 | required: false
18 |
19 | - type: textarea
20 | id: traceback
21 | attributes:
22 | label: Feature Request | 功能请求
23 | description: Feature Request | 功能请求
24 |
--------------------------------------------------------------------------------
/.github/workflows/build-with-all-capacity.yml:
--------------------------------------------------------------------------------
1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
2 | name: build-with-all-capacity
3 |
4 | on:
5 | push:
6 | branches:
7 | - 'master'
8 |
9 | env:
10 | REGISTRY: ghcr.io
11 | IMAGE_NAME: ${{ github.repository }}_with_all_capacity
12 |
13 | jobs:
14 | build-and-push-image:
15 | runs-on: ubuntu-latest
16 | permissions:
17 | contents: read
18 | packages: write
19 |
20 | steps:
21 | - name: Checkout repository
22 | uses: actions/checkout@v3
23 |
24 | - name: Log in to the Container registry
25 | uses: docker/login-action@v2
26 | with:
27 | registry: ${{ env.REGISTRY }}
28 | username: ${{ github.actor }}
29 | password: ${{ secrets.GITHUB_TOKEN }}
30 |
31 | - name: Extract metadata (tags, labels) for Docker
32 | id: meta
33 | uses: docker/metadata-action@v4
34 | with:
35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
36 |
37 | - name: Build and push Docker image
38 | uses: docker/build-push-action@v4
39 | with:
40 | context: .
41 | push: true
42 | file: docs/GithubAction+AllCapacity
43 | tags: ${{ steps.meta.outputs.tags }}
44 | labels: ${{ steps.meta.outputs.labels }}
45 |
--------------------------------------------------------------------------------
/.github/workflows/build-with-audio-assistant.yml:
--------------------------------------------------------------------------------
1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
2 | name: build-with-audio-assistant
3 |
4 | on:
5 | push:
6 | branches:
7 | - 'master'
8 |
9 | env:
10 | REGISTRY: ghcr.io
11 | IMAGE_NAME: ${{ github.repository }}_audio_assistant
12 |
13 | jobs:
14 | build-and-push-image:
15 | runs-on: ubuntu-latest
16 | permissions:
17 | contents: read
18 | packages: write
19 |
20 | steps:
21 | - name: Checkout repository
22 | uses: actions/checkout@v3
23 |
24 | - name: Log in to the Container registry
25 | uses: docker/login-action@v2
26 | with:
27 | registry: ${{ env.REGISTRY }}
28 | username: ${{ github.actor }}
29 | password: ${{ secrets.GITHUB_TOKEN }}
30 |
31 | - name: Extract metadata (tags, labels) for Docker
32 | id: meta
33 | uses: docker/metadata-action@v4
34 | with:
35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
36 |
37 | - name: Build and push Docker image
38 | uses: docker/build-push-action@v4
39 | with:
40 | context: .
41 | push: true
42 | file: docs/GithubAction+NoLocal+AudioAssistant
43 | tags: ${{ steps.meta.outputs.tags }}
44 | labels: ${{ steps.meta.outputs.labels }}
45 |
--------------------------------------------------------------------------------
/.github/workflows/build-with-chatglm.yml:
--------------------------------------------------------------------------------
1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
2 | name: build-with-chatglm
3 |
4 | on:
5 | push:
6 | branches:
7 | - 'master'
8 |
9 | env:
10 | REGISTRY: ghcr.io
11 | IMAGE_NAME: ${{ github.repository }}_chatglm_moss
12 |
13 | jobs:
14 | build-and-push-image:
15 | runs-on: ubuntu-latest
16 | permissions:
17 | contents: read
18 | packages: write
19 |
20 | steps:
21 | - name: Checkout repository
22 | uses: actions/checkout@v3
23 |
24 | - name: Log in to the Container registry
25 | uses: docker/login-action@v2
26 | with:
27 | registry: ${{ env.REGISTRY }}
28 | username: ${{ github.actor }}
29 | password: ${{ secrets.GITHUB_TOKEN }}
30 |
31 | - name: Extract metadata (tags, labels) for Docker
32 | id: meta
33 | uses: docker/metadata-action@v4
34 | with:
35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
36 |
37 | - name: Build and push Docker image
38 | uses: docker/build-push-action@v4
39 | with:
40 | context: .
41 | push: true
42 | file: docs/GithubAction+ChatGLM+Moss
43 | tags: ${{ steps.meta.outputs.tags }}
44 | labels: ${{ steps.meta.outputs.labels }}
45 |
--------------------------------------------------------------------------------
/.github/workflows/build-with-latex-arm.yml:
--------------------------------------------------------------------------------
1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
2 | name: build-with-latex-arm
3 |
4 | on:
5 | push:
6 | branches:
7 | - "master"
8 |
9 | env:
10 | REGISTRY: ghcr.io
11 | IMAGE_NAME: ${{ github.repository }}_with_latex_arm
12 |
13 | jobs:
14 | build-and-push-image:
15 | runs-on: ubuntu-latest
16 | permissions:
17 | contents: read
18 | packages: write
19 |
20 | steps:
21 | - name: Set up QEMU
22 | uses: docker/setup-qemu-action@v3
23 |
24 | - name: Set up Docker Buildx
25 | uses: docker/setup-buildx-action@v3
26 |
27 | - name: Checkout repository
28 | uses: actions/checkout@v4
29 |
30 | - name: Log in to the Container registry
31 | uses: docker/login-action@v3
32 | with:
33 | registry: ${{ env.REGISTRY }}
34 | username: ${{ github.actor }}
35 | password: ${{ secrets.GITHUB_TOKEN }}
36 |
37 | - name: Extract metadata (tags, labels) for Docker
38 | id: meta
39 | uses: docker/metadata-action@v4
40 | with:
41 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
42 |
43 | - name: Build and push Docker image
44 | uses: docker/build-push-action@v6
45 | with:
46 | context: .
47 | push: true
48 | platforms: linux/arm64
49 | file: docs/GithubAction+NoLocal+Latex
50 | tags: ${{ steps.meta.outputs.tags }}
51 | labels: ${{ steps.meta.outputs.labels }}
--------------------------------------------------------------------------------
/.github/workflows/build-with-latex.yml:
--------------------------------------------------------------------------------
1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
2 | name: build-with-latex
3 |
4 | on:
5 | push:
6 | branches:
7 | - 'master'
8 |
9 | env:
10 | REGISTRY: ghcr.io
11 | IMAGE_NAME: ${{ github.repository }}_with_latex
12 |
13 | jobs:
14 | build-and-push-image:
15 | runs-on: ubuntu-latest
16 | permissions:
17 | contents: read
18 | packages: write
19 |
20 | steps:
21 | - name: Checkout repository
22 | uses: actions/checkout@v3
23 |
24 | - name: Log in to the Container registry
25 | uses: docker/login-action@v2
26 | with:
27 | registry: ${{ env.REGISTRY }}
28 | username: ${{ github.actor }}
29 | password: ${{ secrets.GITHUB_TOKEN }}
30 |
31 | - name: Extract metadata (tags, labels) for Docker
32 | id: meta
33 | uses: docker/metadata-action@v4
34 | with:
35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
36 |
37 | - name: Build and push Docker image
38 | uses: docker/build-push-action@v4
39 | with:
40 | context: .
41 | push: true
42 | file: docs/GithubAction+NoLocal+Latex
43 | tags: ${{ steps.meta.outputs.tags }}
44 | labels: ${{ steps.meta.outputs.labels }}
45 |
--------------------------------------------------------------------------------
/.github/workflows/build-without-local-llms.yml:
--------------------------------------------------------------------------------
1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
2 | name: build-without-local-llms
3 |
4 | on:
5 | push:
6 | branches:
7 | - 'master'
8 |
9 | env:
10 | REGISTRY: ghcr.io
11 | IMAGE_NAME: ${{ github.repository }}_nolocal
12 |
13 | jobs:
14 | build-and-push-image:
15 | runs-on: ubuntu-latest
16 | permissions:
17 | contents: read
18 | packages: write
19 |
20 | steps:
21 | - name: Checkout repository
22 | uses: actions/checkout@v3
23 |
24 | - name: Log in to the Container registry
25 | uses: docker/login-action@v2
26 | with:
27 | registry: ${{ env.REGISTRY }}
28 | username: ${{ github.actor }}
29 | password: ${{ secrets.GITHUB_TOKEN }}
30 |
31 | - name: Extract metadata (tags, labels) for Docker
32 | id: meta
33 | uses: docker/metadata-action@v4
34 | with:
35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
36 |
37 | - name: Build and push Docker image
38 | uses: docker/build-push-action@v4
39 | with:
40 | context: .
41 | push: true
42 | file: docs/GithubAction+NoLocal
43 | tags: ${{ steps.meta.outputs.tags }}
44 | labels: ${{ steps.meta.outputs.labels }}
45 |
--------------------------------------------------------------------------------
/.github/workflows/conda-pack-windows.yml:
--------------------------------------------------------------------------------
1 | name: Create Conda Environment Package
2 |
3 | on:
4 | workflow_dispatch:
5 |
6 | jobs:
7 | build:
8 | runs-on: windows-latest
9 |
10 | steps:
11 | - name: Checkout repository
12 | uses: actions/checkout@v4
13 |
14 | - name: Setup Miniconda
15 | uses: conda-incubator/setup-miniconda@v3
16 | with:
17 | auto-activate-base: true
18 | activate-environment: ""
19 |
20 | - name: Create new Conda environment
21 | shell: bash -l {0}
22 | run: |
23 | conda create -n gpt python=3.11 -y
24 | conda activate gpt
25 |
26 | - name: Install requirements
27 | shell: bash -l {0}
28 | run: |
29 | conda activate gpt
30 | pip install -r requirements.txt
31 |
32 | - name: Install conda-pack
33 | shell: bash -l {0}
34 | run: |
35 | conda activate gpt
36 | conda install conda-pack -y
37 |
38 | - name: Pack conda environment
39 | shell: bash -l {0}
40 | run: |
41 | conda activate gpt
42 | conda pack -n gpt -o gpt.tar.gz
43 |
44 | - name: Create workspace zip
45 | shell: pwsh
46 | run: |
47 | mkdir workspace
48 | Get-ChildItem -Exclude "workspace" | Copy-Item -Destination workspace -Recurse
49 | Remove-Item -Path workspace/.git* -Recurse -Force -ErrorAction SilentlyContinue
50 | Copy-Item gpt.tar.gz workspace/ -Force
51 |
52 | - name: Upload packed files
53 | uses: actions/upload-artifact@v4
54 | with:
55 | name: gpt-academic-package
56 | path: workspace
57 |
--------------------------------------------------------------------------------
/.github/workflows/stale.yml:
--------------------------------------------------------------------------------
1 | # This workflow warns and then closes issues and PRs that have had no activity for a specified amount of time.
2 | #
3 | # You can adjust the behavior by modifying this file.
4 | # For more information, see:
5 | # https://github.com/actions/stale
6 |
7 | name: 'Close stale issues and PRs'
8 | on:
9 | schedule:
10 | - cron: '*/30 * * * *'
11 |
12 | jobs:
13 | stale:
14 | runs-on: ubuntu-latest
15 | permissions:
16 | issues: write
17 | pull-requests: read
18 |
19 | steps:
20 | - uses: actions/stale@v8
21 | with:
22 | stale-issue-message: 'This issue is stale because it has been open 100 days with no activity. Remove stale label or comment or this will be closed in 7 days.'
23 | days-before-stale: 100
24 | days-before-close: 7
25 |
--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
1 | # Byte-compiled / optimized / DLL files
2 | __pycache__/
3 | *.py[cod]
4 | *$py.class
5 |
6 | # C extensions
7 | *.so
8 |
9 | # Distribution / packaging
10 | .Python
11 | build/
12 | develop-eggs/
13 | dist/
14 | downloads/
15 | eggs/
16 | .eggs/
17 | lib/
18 | lib64/
19 | parts/
20 | sdist/
21 | var/
22 | wheels/
23 | pip-wheel-metadata/
24 | share/python-wheels/
25 | *.egg-info/
26 | .installed.cfg
27 | *.egg
28 | MANIFEST
29 |
30 | # PyInstaller
31 | # Usually these files are written by a python script from a template
32 | # before PyInstaller builds the exe, so as to inject date/other infos into it.
33 | *.manifest
34 | *.spec
35 | # Installer logs
36 | pip-log.txt
37 | pip-delete-this-directory.txt
38 |
39 | # Unit test / coverage reports
40 | htmlcov/
41 | .tox/
42 | .nox/
43 | .coverage
44 | .coverage.*
45 | .cache
46 | nosetests.xml
47 | coverage.xml
48 | *.cover
49 | *.py,cover
50 | .hypothesis/
51 | .pytest_cache/
52 |
53 | # Translations
54 | *.mo
55 | *.pot
56 | github
57 | .github
58 | TEMP
59 | TRASH
60 |
61 | # Django stuff:
62 | *.log
63 | local_settings.py
64 | db.sqlite3
65 | db.sqlite3-journal
66 |
67 | # Flask stuff:
68 | instance/
69 | .webassets-cache
70 |
71 | # Scrapy stuff:
72 | .scrapy
73 |
74 | # Sphinx documentation
75 | docs/_build/
76 |
77 | # PyBuilder
78 | target/
79 |
80 | # Jupyter Notebook
81 | .ipynb_checkpoints
82 |
83 | # IPython
84 | profile_default/
85 | ipython_config.py
86 |
87 | # pyenv
88 | .python-version
89 |
90 | # pipenv
91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies
93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not
94 | # install all needed dependencies.
95 | #Pipfile.lock
96 |
97 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow
98 | __pypackages__/
99 |
100 | # Celery stuff
101 | celerybeat-schedule
102 | celerybeat.pid
103 |
104 | # SageMath parsed files
105 | *.sage.py
106 |
107 | # Environments
108 | .env
109 | .venv
110 | env/
111 | venv/
112 | ENV/
113 | env.bak/
114 | venv.bak/
115 |
116 | # Spyder project settings
117 | .spyderproject
118 | .spyproject
119 |
120 | # Rope project settings
121 | .ropeproject
122 |
123 | # mkdocs documentation
124 | /site
125 |
126 | # mypy
127 | .mypy_cache/
128 | .dmypy.json
129 | dmypy.json
130 |
131 | # Pyre type checker
132 | .pyre/
133 |
134 | # macOS files
135 | .DS_Store
136 |
137 | .vscode
138 | .idea
139 |
140 | history
141 | ssr_conf
142 | config_private.py
143 | gpt_log
144 | private.md
145 | private_upload
146 | other_llms
147 | cradle*
148 | debug*
149 | private*
150 | crazy_functions/test_project/pdf_and_word
151 | crazy_functions/test_samples
152 | request_llms/jittorllms
153 | multi-language
154 | request_llms/moss
155 | media
156 | flagged
157 | request_llms/ChatGLM-6b-onnx-u8s8
158 | .pre-commit-config.yaml
159 | test.*
160 | temp.*
161 | objdump*
162 | *.min.*.js
163 | TODO
164 | experimental_mods
165 | search_results
166 |
--------------------------------------------------------------------------------
/Dockerfile:
--------------------------------------------------------------------------------
1 | # 此Dockerfile适用于“无本地模型”的迷你运行环境构建
2 | # 如果需要使用chatglm等本地模型或者latex运行依赖，请参考 docker-compose.yml
3 | # - 如何构建: 先修改 `config.py`， 然后 `docker build -t gpt-academic . `
4 | # - 如何运行(Linux下): `docker run --rm -it --net=host gpt-academic `
5 | # - 如何运行(其他操作系统，选择任意一个固定端口50923): `docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic `
6 |
7 | FROM ghcr.io/astral-sh/uv:python3.12-bookworm
8 |
9 | # 非必要步骤，更换pip源 （以下三行，可以删除）
10 | RUN echo '[global]' > /etc/pip.conf && \
11 | echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
12 | echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
13 |
14 | # 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除）
15 | RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
16 | sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
17 | apt-get update
18 | RUN apt-get install ffmpeg -y
19 | RUN apt-get clean
20 |
21 | # 进入工作路径（必要）
22 | WORKDIR /gpt
23 |
24 | # 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除）
25 | COPY requirements.txt ./
26 | RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
27 | ENV PATH="/gpt/.venv/bin:$PATH"
28 | RUN python -c 'import loguru'
29 |
30 | # 装载项目文件，安装剩余依赖（必要）
31 | COPY . .
32 | RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
33 |
34 | # # 非必要步骤，用于预热模块（可以删除）
35 | RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()'
36 |
37 | # 启动（必要）
38 | CMD ["bash", "-c", "python main.py"]
39 |
--------------------------------------------------------------------------------
/crazy_functions/Image_Generate_Wrap.py:
--------------------------------------------------------------------------------
1 |
2 | from toolbox import get_conf, update_ui
3 | from crazy_functions.Image_Generate import 图片生成_DALLE2, 图片生成_DALLE3, 图片修改_DALLE2
4 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
5 |
6 |
7 | class ImageGen_Wrap(GptAcademicPluginTemplate):
8 | def __init__(self):
9 | """
10 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！
11 | """
12 | pass
13 |
14 | def define_arg_selection_menu(self):
15 | """
16 | 定义插件的二级选项菜单
17 |
18 | 第一个参数，名称`main_input`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值；
19 | 第二个参数，名称`advanced_arg`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值；
20 |
21 | """
22 | gui_definition = {
23 | "main_input":
24 | ArgProperty(title="输入图片描述", description="需要生成图像的文本描述，尽量使用英文", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
25 | "model_name":
26 | ArgProperty(title="模型", options=["DALLE2", "DALLE3"], default_value="DALLE3", description="无", type="dropdown").model_dump_json(),
27 | "resolution":
28 | ArgProperty(title="分辨率", options=["256x256(限DALLE2)", "512x512(限DALLE2)", "1024x1024", "1792x1024(限DALLE3)", "1024x1792(限DALLE3)"], default_value="1024x1024", description="无", type="dropdown").model_dump_json(),
29 | "quality (仅DALLE3生效)":
30 | ArgProperty(title="质量", options=["standard", "hd"], default_value="standard", description="无", type="dropdown").model_dump_json(),
31 | "style (仅DALLE3生效)":
32 | ArgProperty(title="风格", options=["vivid", "natural"], default_value="vivid", description="无", type="dropdown").model_dump_json(),
33 |
34 | }
35 | return gui_definition
36 |
37 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
38 | """
39 | 执行插件
40 | """
41 | # 分辨率
42 | resolution = plugin_kwargs["resolution"].replace("(限DALLE2)", "").replace("(限DALLE3)", "")
43 |
44 | if plugin_kwargs["model_name"] == "DALLE2":
45 | plugin_kwargs["advanced_arg"] = resolution
46 | yield from 图片生成_DALLE2(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
47 |
48 | elif plugin_kwargs["model_name"] == "DALLE3":
49 | quality = plugin_kwargs["quality (仅DALLE3生效)"]
50 | style = plugin_kwargs["style (仅DALLE3生效)"]
51 | plugin_kwargs["advanced_arg"] = f"{resolution}-{quality}-{style}"
52 | yield from 图片生成_DALLE3(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
53 |
54 | else:
55 | chatbot.append([None, "抱歉，找不到该模型"])
56 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
57 |
--------------------------------------------------------------------------------
/crazy_functions/Internet_GPT_Wrap.py:
--------------------------------------------------------------------------------
1 | import random
2 | from toolbox import get_conf
3 | from crazy_functions.Internet_GPT import 连接网络回答问题
4 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
5 |
6 |
7 | class NetworkGPT_Wrap(GptAcademicPluginTemplate):
8 | def __init__(self):
9 | """
10 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！
11 | """
12 | pass
13 |
14 | def define_arg_selection_menu(self):
15 | """
16 | 定义插件的二级选项菜单
17 |
18 | 第一个参数，名称`main_input`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值；
19 | 第二个参数，名称`advanced_arg`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值；
20 | 第三个参数，名称`allow_cache`，参数`type`声明这是一个下拉菜单，下拉菜单上方显示`title`+`description`，下拉菜单的选项为`options`，`default_value`为下拉菜单默认值；
21 |
22 | """
23 | urls = get_conf("SEARXNG_URLS")
24 | url = random.choice(urls)
25 |
26 | gui_definition = {
27 | "main_input":
28 | ArgProperty(title="输入问题", description="待通过互联网检索的问题，会自动读取输入框内容", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
29 | "categories":
30 | ArgProperty(title="搜索分类", options=["网页", "学术论文"], default_value="网页", description="无", type="dropdown").model_dump_json(),
31 | "engine":
32 | ArgProperty(title="选择搜索引擎", options=["Mixed", "bing", "google", "duckduckgo"], default_value="google", description="无", type="dropdown").model_dump_json(),
33 | "optimizer":
34 | ArgProperty(title="搜索优化", options=["关闭", "开启", "开启(增强)"], default_value="关闭", description="是否使用搜索增强。注意这可能会消耗较多token", type="dropdown").model_dump_json(),
35 | "searxng_url":
36 | ArgProperty(title="Searxng服务地址", description="输入Searxng的地址", default_value=url, type="string").model_dump_json(), # 主输入，自动从输入框同步
37 |
38 | }
39 | return gui_definition
40 |
41 | def execute(txt, llm_kwargs, plugin_kwargs:dict, chatbot, history, system_prompt, user_request):
42 | """
43 | 执行插件
44 | """
45 | if plugin_kwargs.get("categories", None) == "网页": plugin_kwargs["categories"] = "general"
46 | elif plugin_kwargs.get("categories", None) == "学术论文": plugin_kwargs["categories"] = "science"
47 | else: plugin_kwargs["categories"] = "general"
48 | yield from 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
49 |
50 |
--------------------------------------------------------------------------------
/crazy_functions/PDF_Translate_Wrap.py:
--------------------------------------------------------------------------------
1 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
2 | from .PDF_Translate import 批量翻译PDF文档
3 |
4 |
5 | class PDF_Tran(GptAcademicPluginTemplate):
6 | def __init__(self):
7 | """
8 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！
9 | """
10 | pass
11 |
12 | def define_arg_selection_menu(self):
13 | """
14 | 定义插件的二级选项菜单
15 | """
16 | gui_definition = {
17 | "main_input":
18 | ArgProperty(title="PDF文件路径", description="未指定路径，请上传文件后，再点击该插件", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
19 | "additional_prompt":
20 | ArgProperty(title="额外提示词", description="例如：对专有名词、翻译语气等方面的要求", default_value="", type="string").model_dump_json(), # 高级参数输入区，自动同步
21 | "pdf_parse_method":
22 | ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "Classic"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
23 | }
24 | return gui_definition
25 |
26 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
27 | """
28 | 执行插件
29 | """
30 | main_input = plugin_kwargs["main_input"]
31 | additional_prompt = plugin_kwargs["additional_prompt"]
32 | pdf_parse_method = plugin_kwargs["pdf_parse_method"]
33 | yield from 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
--------------------------------------------------------------------------------
/crazy_functions/SourceCode_Comment_Wrap.py:
--------------------------------------------------------------------------------
1 |
2 | from toolbox import get_conf, update_ui
3 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
4 | from crazy_functions.SourceCode_Comment import 注释Python项目
5 |
6 | class SourceCodeComment_Wrap(GptAcademicPluginTemplate):
7 | def __init__(self):
8 | """
9 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！
10 | """
11 | pass
12 |
13 | def define_arg_selection_menu(self):
14 | """
15 | 定义插件的二级选项菜单
16 | """
17 | gui_definition = {
18 | "main_input":
19 | ArgProperty(title="路径", description="程序路径（上传文件后自动填写）", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
20 | "use_chinese":
21 | ArgProperty(title="注释语言", options=["英文", "中文"], default_value="英文", description="无", type="dropdown").model_dump_json(),
22 | # "use_emoji":
23 | # ArgProperty(title="在注释中使用emoji", options=["禁止", "允许"], default_value="禁止", description="无", type="dropdown").model_dump_json(),
24 | }
25 | return gui_definition
26 |
27 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
28 | """
29 | 执行插件
30 | """
31 | if plugin_kwargs["use_chinese"] == "中文":
32 | plugin_kwargs["use_chinese"] = True
33 | else:
34 | plugin_kwargs["use_chinese"] = False
35 |
36 | yield from 注释Python项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
37 |
--------------------------------------------------------------------------------
/crazy_functions/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/crazy_functions/__init__.py
--------------------------------------------------------------------------------
/crazy_functions/agent_fns/auto_agent.py:
--------------------------------------------------------------------------------
1 | from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
2 | from toolbox import report_exception, get_log_folder, update_ui_latest_msg, Singleton
3 | from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
4 | from crazy_functions.agent_fns.general import AutoGenGeneral
5 |
6 |
7 |
8 | class AutoGenMath(AutoGenGeneral):
9 |
10 | def define_agents(self):
11 | from autogen import AssistantAgent, UserProxyAgent
12 | return [
13 | {
14 | "name": "assistant", # name of the agent.
15 | "cls": AssistantAgent, # class of the agent.
16 | },
17 | {
18 | "name": "user_proxy", # name of the agent.
19 | "cls": UserProxyAgent, # class of the agent.
20 | "human_input_mode": "ALWAYS", # always ask for human input.
21 | "llm_config": False, # disables llm-based auto reply.
22 | },
23 | ]
--------------------------------------------------------------------------------
/crazy_functions/agent_fns/echo_agent.py:
--------------------------------------------------------------------------------
1 | from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
2 | from loguru import logger
3 |
4 | class EchoDemo(PluginMultiprocessManager):
5 | def subprocess_worker(self, child_conn):
6 | # ⭐⭐ 子进程
7 | self.child_conn = child_conn
8 | while True:
9 | msg = self.child_conn.recv() # PipeCom
10 | if msg.cmd == "user_input":
11 | # wait father user input
12 | self.child_conn.send(PipeCom("show", msg.content))
13 | wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.")
14 | if not wait_success:
15 | # wait timeout, terminate this subprocess_worker
16 | break
17 | elif msg.cmd == "terminate":
18 | self.child_conn.send(PipeCom("done", ""))
19 | break
20 | logger.info('[debug] subprocess_worker terminated')
--------------------------------------------------------------------------------
/crazy_functions/agent_fns/persistent.py:
--------------------------------------------------------------------------------
1 | from toolbox import Singleton
2 | @Singleton
3 | class GradioMultiuserManagerForPersistentClasses():
4 | def __init__(self):
5 | self.mapping = {}
6 |
7 | def already_alive(self, key):
8 | return (key in self.mapping) and (self.mapping[key].is_alive())
9 |
10 | def set(self, key, x):
11 | self.mapping[key] = x
12 | return self.mapping[key]
13 |
14 | def get(self, key):
15 | return self.mapping[key]
16 |
17 |
--------------------------------------------------------------------------------
/crazy_functions/agent_fns/python_comment_compare.html:
--------------------------------------------------------------------------------
1 | <!DOCTYPE html>
2 | <html lang="zh-CN">
3 | <head>
4 | <style>ADVANCED_CSS</style>
5 | <meta charset="UTF-8">
6 | <title>源文件对比</title>
7 | <style>
8 | body {
9 | font-family: Arial, sans-serif;
10 | display: flex;
11 | justify-content: center;
12 | align-items: center;
13 | height: 100vh;
14 | margin: 0;
15 | }
16 | .container {
17 | display: flex;
18 | width: 95%;
19 | height: -webkit-fill-available;
20 | }
21 | .code-container {
22 | flex: 1;
23 | margin: 0px;
24 | padding: 0px;
25 | border: 1px solid #ccc;
26 | background-color: #f9f9f9;
27 | overflow: auto;
28 | }
29 | pre {
30 | white-space: pre-wrap;
31 | word-wrap: break-word;
32 | }
33 | </style>
34 | </head>
35 | <body>
36 | <div class="container">
37 | <div class="code-container">
38 | REPLACE_CODE_FILE_LEFT
39 | </div>
40 | <div class="code-container">
41 | REPLACE_CODE_FILE_RIGHT
42 | </div>
43 | </div>
44 | </body>
45 | </html>
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/crazy_functions/agent_fns/watchdog.py:
--------------------------------------------------------------------------------
1 | import threading, time
2 | from loguru import logger
3 |
4 | class WatchDog():
5 | def __init__(self, timeout, bark_fn, interval=3, msg="") -> None:
6 | self.last_feed = None
7 | self.timeout = timeout
8 | self.bark_fn = bark_fn
9 | self.interval = interval
10 | self.msg = msg
11 | self.kill_dog = False
12 |
13 | def watch(self):
14 | while True:
15 | if self.kill_dog: break
16 | if time.time() - self.last_feed > self.timeout:
17 | if len(self.msg) > 0: logger.info(self.msg)
18 | self.bark_fn()
19 | break
20 | time.sleep(self.interval)
21 |
22 | def begin_watch(self):
23 | self.last_feed = time.time()
24 | th = threading.Thread(target=self.watch)
25 | th.daemon = True
26 | th.start()
27 |
28 | def feed(self):
29 | self.last_feed = time.time()
30 |
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/crazy_functions/ast_fns/comment_remove.py:
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1 | import token
2 | import tokenize
3 | import copy
4 | import io
5 |
6 |
7 | def remove_python_comments(input_source: str) -> str:
8 | source_flag = copy.copy(input_source)
9 | source = io.StringIO(input_source)
10 | ls = input_source.split('\n')
11 | prev_toktype = token.INDENT
12 | readline = source.readline
13 |
14 | def get_char_index(lineno, col):
15 | # find the index of the char in the source code
16 | if lineno == 1:
17 | return len('\n'.join(ls[:(lineno-1)])) + col
18 | else:
19 | return len('\n'.join(ls[:(lineno-1)])) + col + 1
20 |
21 | def replace_char_between(start_lineno, start_col, end_lineno, end_col, source, replace_char, ls):
22 | # replace char between start_lineno, start_col and end_lineno, end_col with replace_char, but keep '\n' and ' '
23 | b = get_char_index(start_lineno, start_col)
24 | e = get_char_index(end_lineno, end_col)
25 | for i in range(b, e):
26 | if source[i] == '\n':
27 | source = source[:i] + '\n' + source[i+1:]
28 | elif source[i] == ' ':
29 | source = source[:i] + ' ' + source[i+1:]
30 | else:
31 | source = source[:i] + replace_char + source[i+1:]
32 | return source
33 |
34 | tokgen = tokenize.generate_tokens(readline)
35 | for toktype, ttext, (slineno, scol), (elineno, ecol), ltext in tokgen:
36 | if toktype == token.STRING and (prev_toktype == token.INDENT):
37 | source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls)
38 | elif toktype == token.STRING and (prev_toktype == token.NEWLINE):
39 | source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls)
40 | elif toktype == tokenize.COMMENT:
41 | source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls)
42 | prev_toktype = toktype
43 | return source_flag
44 |
45 |
46 | # 示例使用
47 | if __name__ == "__main__":
48 | with open("source.py", "r", encoding="utf-8") as f:
49 | source_code = f.read()
50 |
51 | cleaned_code = remove_python_comments(source_code)
52 |
53 | with open("cleaned_source.py", "w", encoding="utf-8") as f:
54 | f.write(cleaned_code)
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/crazy_functions/doc_fns/__init__.py:
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https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/crazy_functions/doc_fns/__init__.py
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/crazy_functions/doc_fns/conversation_doc/markdown_doc.py:
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1 |
2 | class MarkdownFormatter:
3 | """Markdown格式文档生成器 - 用于生成对话记录的markdown文档"""
4 |
5 | def __init__(self):
6 | self.content = []
7 |
8 | def _add_content(self, text: str):
9 | """添加正文内容"""
10 | if text:
11 | self.content.append(f"\n{text}\n")
12 |
13 | def create_document(self, history: list) -> str:
14 | """
15 | 创建完整的Markdown文档
16 | Args:
17 | history: 历史记录列表，偶数位置为问题，奇数位置为答案
18 | Returns:
19 | str: 生成的Markdown文本
20 | """
21 | self.content = []
22 |
23 | # 处理问答对
24 | for i in range(0, len(history), 2):
25 | question = history[i]
26 | answer = history[i + 1]
27 |
28 | # 添加问题
29 | self.content.append(f"\n### 问题 {i//2 + 1}")
30 | self._add_content(question)
31 |
32 | # 添加回答
33 | self.content.append(f"\n### 回答 {i//2 + 1}")
34 | self._add_content(answer)
35 |
36 | # 添加分隔线
37 | self.content.append("\n---\n")
38 |
39 | return "\n".join(self.content)
40 |
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/crazy_functions/doc_fns/conversation_doc/txt_doc.py:
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1 |
2 | import re
3 |
4 |
5 | def convert_markdown_to_txt(markdown_text):
6 | """Convert markdown text to plain text while preserving formatting"""
7 | # Standardize line endings
8 | markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n')
9 |
10 | # 1. Handle headers but keep their formatting instead of removing them
11 | markdown_text = re.sub(r'^#\s+(.+)#39;, r'# \1', markdown_text, flags=re.MULTILINE)
12 | markdown_text = re.sub(r'^##\s+(.+)#39;, r'## \1', markdown_text, flags=re.MULTILINE)
13 | markdown_text = re.sub(r'^###\s+(.+)#39;, r'### \1', markdown_text, flags=re.MULTILINE)
14 |
15 | # 2. Handle bold and italic - simply remove markers
16 | markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text)
17 | markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text)
18 |
19 | # 3. Handle lists but preserve formatting
20 | markdown_text = re.sub(r'^\s*[-*+]\s+(.+?)(?=\n|$)', r'• \1', markdown_text, flags=re.MULTILINE)
21 |
22 | # 4. Handle links - keep only the text
23 | markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+)\)', r'\1 (\2)', markdown_text)
24 |
25 | # 5. Handle HTML links - convert to user-friendly format
26 | markdown_text = re.sub(r'<a href=[\'"]([^\'"]+)[\'"](?:\s+target=[\'"][^\'"]+[\'"])?>([^<]+)</a>', r'\2 (\1)',
27 | markdown_text)
28 |
29 | # 6. Preserve paragraph breaks
30 | markdown_text = re.sub(r'\n{3,}', '\n\n', markdown_text) # normalize multiple newlines to double newlines
31 |
32 | # 7. Clean up extra spaces but maintain indentation
33 | markdown_text = re.sub(r' +', ' ', markdown_text)
34 |
35 | return markdown_text.strip()
36 |
37 |
38 | class TxtFormatter:
39 | """Chat history TXT document generator"""
40 |
41 | def __init__(self):
42 | self.content = []
43 | self._setup_document()
44 |
45 | def _setup_document(self):
46 | """Initialize document with header"""
47 | self.content.append("=" * 50)
48 | self.content.append("GPT-Academic对话记录".center(48))
49 | self.content.append("=" * 50)
50 |
51 | def _format_header(self):
52 | """Create document header with current date"""
53 | from datetime import datetime
54 | date_str = datetime.now().strftime('%Y年%m月%d日')
55 | return [
56 | date_str.center(48),
57 | "\n" # Add blank line after date
58 | ]
59 |
60 | def create_document(self, history):
61 | """Generate document from chat history"""
62 | # Add header with date
63 | self.content.extend(self._format_header())
64 |
65 | # Add conversation content
66 | for i in range(0, len(history), 2):
67 | question = history[i]
68 | answer = convert_markdown_to_txt(history[i + 1]) if i + 1 < len(history) else ""
69 |
70 | if question:
71 | self.content.append(f"问题 {i // 2 + 1}：{str(question)}")
72 | self.content.append("") # Add blank line
73 |
74 | if answer:
75 | self.content.append(f"回答 {i // 2 + 1}：{str(answer)}")
76 | self.content.append("") # Add blank line
77 |
78 | # Join all content with newlines
79 | return "\n".join(self.content)
80 |
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/crazy_functions/doc_fns/read_fns/__init__.py:
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https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/crazy_functions/doc_fns/read_fns/__init__.py
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/crazy_functions/doc_fns/read_fns/docx_reader.py:
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1 | import nltk
2 | nltk.data.path.append('~/nltk_data')
3 | nltk.download('averaged_perceptron_tagger', download_dir='~/nltk_data',
4 | )
5 | nltk.download('punkt', download_dir='~/nltk_data',
6 | )
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/crazy_functions/doc_fns/read_fns/unstructured_all/__init__.py:
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https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/crazy_functions/doc_fns/read_fns/unstructured_all/__init__.py
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/crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_md.py:
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1 | from pathlib import Path
2 | from crazy_functions.doc_fns.read_fns.unstructured_all.paper_structure_extractor import PaperStructureExtractor
3 |
4 | def extract_and_save_as_markdown(paper_path, output_path=None):
5 | """
6 | 提取论文结构并保存为Markdown格式
7 |
8 | 参数:
9 | paper_path: 论文文件路径
10 | output_path: 输出的Markdown文件路径，如果不指定，将使用与输入相同的文件名但扩展名为.md
11 |
12 | 返回:
13 | 保存的Markdown文件路径
14 | """
15 | # 创建提取器
16 | extractor = PaperStructureExtractor()
17 |
18 | # 解析文件路径
19 | paper_path = Path(paper_path)
20 |
21 | # 如果未指定输出路径，使用相同文件名但扩展名为.md
22 | if output_path is None:
23 | output_path = paper_path.with_suffix('.md')
24 | else:
25 | output_path = Path(output_path)
26 |
27 | # 确保输出目录存在
28 | output_path.parent.mkdir(parents=True, exist_ok=True)
29 |
30 | print(f"正在处理论文: {paper_path}")
31 |
32 | try:
33 | # 提取论文结构
34 | paper = extractor.extract_paper_structure(paper_path)
35 |
36 | # 生成Markdown内容
37 | markdown_content = extractor.generate_markdown(paper)
38 |
39 | # 保存到文件
40 | with open(output_path, 'w', encoding='utf-8') as f:
41 | f.write(markdown_content)
42 |
43 | print(f"已成功保存Markdown文件: {output_path}")
44 |
45 | # 打印摘要信息
46 | print("\n论文摘要信息:")
47 | print(f"标题: {paper.metadata.title}")
48 | print(f"作者: {', '.join(paper.metadata.authors)}")
49 | print(f"关键词: {', '.join(paper.keywords)}")
50 | print(f"章节数: {len(paper.sections)}")
51 | print(f"图表数: {len(paper.figures)}")
52 | print(f"表格数: {len(paper.tables)}")
53 | print(f"公式数: {len(paper.formulas)}")
54 | print(f"参考文献数: {len(paper.references)}")
55 |
56 | return output_path
57 |
58 | except Exception as e:
59 | print(f"处理论文时出错: {e}")
60 | import traceback
61 | traceback.print_exc()
62 | return None
63 |
64 | # 使用示例
65 | if __name__ == "__main__":
66 | # 替换为实际的论文文件路径
67 | sample_paper = "crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf"
68 |
69 | # 可以指定输出路径，也可以使用默认路径
70 | # output_file = "/path/to/output/paper_structure.md"
71 | # extract_and_save_as_markdown(sample_paper, output_file)
72 |
73 | # 使用默认输出路径（与输入文件同名但扩展名为.md）
74 | extract_and_save_as_markdown(sample_paper)
75 |
76 | # # 批量处理多个论文的示例
77 | # paper_dir = Path("/path/to/papers/folder")
78 | # output_dir = Path("/path/to/output/folder")
79 | #
80 | # # 确保输出目录存在
81 | # output_dir.mkdir(parents=True, exist_ok=True)
82 | #
83 | # # 处理目录中的所有PDF文件
84 | # for paper_file in paper_dir.glob("*.pdf"):
85 | # output_file = output_dir / f"{paper_file.stem}.md"
86 | # extract_and_save_as_markdown(paper_file, output_file)
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/crazy_functions/game_fns/game_ascii_art.py:
--------------------------------------------------------------------------------
1 | from toolbox import CatchException, update_ui, update_ui_latest_msg
2 | from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
3 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
4 | from request_llms.bridge_all import predict_no_ui_long_connection
5 | from crazy_functions.game_fns.game_utils import get_code_block, is_same_thing
6 | import random
7 |
8 |
9 | class MiniGame_ASCII_Art(GptAcademicGameBaseState):
10 | def step(self, prompt, chatbot, history):
11 | if self.step_cnt == 0:
12 | chatbot.append(["我画你猜（动物）", "请稍等..."])
13 | else:
14 | if prompt.strip() == 'exit':
15 | self.delete_game = True
16 | yield from update_ui_latest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
17 | return
18 | chatbot.append([prompt, ""])
19 | yield from update_ui(chatbot=chatbot, history=history)
20 |
21 | if self.step_cnt == 0:
22 | self.lock_plugin(chatbot)
23 | self.cur_task = 'draw'
24 |
25 | if self.cur_task == 'draw':
26 | avail_obj = ["狗","猫","鸟","鱼","老鼠","蛇"]
27 | self.obj = random.choice(avail_obj)
28 | inputs = "I want to play a game called Guess the ASCII art. You can draw the ASCII art and I will try to guess it. " + \
29 | f"This time you draw a {self.obj}. Note that you must not indicate what you have draw in the text, and you should only produce the ASCII art wrapped by ```. "
30 | raw_res = predict_no_ui_long_connection(inputs=inputs, llm_kwargs=self.llm_kwargs, history=[], sys_prompt="")
31 | self.cur_task = 'identify user guess'
32 | res = get_code_block(raw_res)
33 | history += ['', f'the answer is {self.obj}', inputs, res]
34 | yield from update_ui_latest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
35 |
36 | elif self.cur_task == 'identify user guess':
37 | if is_same_thing(self.obj, prompt, self.llm_kwargs):
38 | self.delete_game = True
39 | yield from update_ui_latest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
40 | else:
41 | self.cur_task = 'identify user guess'
42 | yield from update_ui_latest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
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/crazy_functions/game_fns/game_utils.py:
--------------------------------------------------------------------------------
1 |
2 | from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
3 | from request_llms.bridge_all import predict_no_ui_long_connection
4 | def get_code_block(reply):
5 | import re
6 | pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
7 | matches = re.findall(pattern, reply) # find all code blocks in text
8 | if len(matches) == 1:
9 | return "```" + matches[0] + "```" # code block
10 | raise RuntimeError("GPT is not generating proper code.")
11 |
12 | def is_same_thing(a, b, llm_kwargs):
13 | from pydantic import BaseModel, Field
14 | class IsSameThing(BaseModel):
15 | is_same_thing: bool = Field(description="determine whether two objects are same thing.", default=False)
16 |
17 | def run_gpt_fn(inputs, sys_prompt, history=[]):
18 | return predict_no_ui_long_connection(
19 | inputs=inputs, llm_kwargs=llm_kwargs,
20 | history=history, sys_prompt=sys_prompt, observe_window=[]
21 | )
22 |
23 | gpt_json_io = GptJsonIO(IsSameThing)
24 | inputs_01 = "Identity whether the user input and the target is the same thing: \n target object: {a} \n user input object: {b} \n\n\n".format(a=a, b=b)
25 | inputs_01 += "\n\n\n Note that the user may describe the target object with a different language, e.g. cat and 猫 are the same thing."
26 | analyze_res_cot_01 = run_gpt_fn(inputs_01, "", [])
27 |
28 | inputs_02 = inputs_01 + gpt_json_io.format_instructions
29 | analyze_res = run_gpt_fn(inputs_02, "", [inputs_01, analyze_res_cot_01])
30 |
31 | try:
32 | res = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
33 | return res.is_same_thing
34 | except JsonStringError as e:
35 | return False
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/crazy_functions/gen_fns/gen_fns_shared.py:
--------------------------------------------------------------------------------
1 | import time
2 | import importlib
3 | from toolbox import trimmed_format_exc, gen_time_str, get_log_folder
4 | from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
5 | from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
6 | import multiprocessing
7 |
8 | def get_class_name(class_string):
9 | import re
10 | # Use regex to extract the class name
11 | class_name = re.search(r'class (\w+)\(', class_string).group(1)
12 | return class_name
13 |
14 | def try_make_module(code, chatbot):
15 | module_file = 'gpt_fn_' + gen_time_str().replace('-','_')
16 | fn_path = f'{get_log_folder(plugin_name="gen_plugin_verify")}/{module_file}.py'
17 | with open(fn_path, 'w', encoding='utf8') as f: f.write(code)
18 | promote_file_to_downloadzone(fn_path, chatbot=chatbot)
19 | class_name = get_class_name(code)
20 | manager = multiprocessing.Manager()
21 | return_dict = manager.dict()
22 | p = multiprocessing.Process(target=is_function_successfully_generated, args=(fn_path, class_name, return_dict))
23 | # only has 10 seconds to run
24 | p.start(); p.join(timeout=10)
25 | if p.is_alive(): p.terminate(); p.join()
26 | p.close()
27 | return return_dict["success"], return_dict['traceback']
28 |
29 | # check is_function_successfully_generated
30 | def is_function_successfully_generated(fn_path, class_name, return_dict):
31 | return_dict['success'] = False
32 | return_dict['traceback'] = ""
33 | try:
34 | # Create a spec for the module
35 | module_spec = importlib.util.spec_from_file_location('example_module', fn_path)
36 | # Load the module
37 | example_module = importlib.util.module_from_spec(module_spec)
38 | module_spec.loader.exec_module(example_module)
39 | # Now you can use the module
40 | some_class = getattr(example_module, class_name)
41 | # Now you can create an instance of the class
42 | instance = some_class()
43 | return_dict['success'] = True
44 | return
45 | except:
46 | return_dict['traceback'] = trimmed_format_exc()
47 | return
48 |
49 | def subprocess_worker(code, file_path, return_dict):
50 | return_dict['result'] = None
51 | return_dict['success'] = False
52 | return_dict['traceback'] = ""
53 | try:
54 | module_file = 'gpt_fn_' + gen_time_str().replace('-','_')
55 | fn_path = f'{get_log_folder(plugin_name="gen_plugin_run")}/{module_file}.py'
56 | with open(fn_path, 'w', encoding='utf8') as f: f.write(code)
57 | class_name = get_class_name(code)
58 | # Create a spec for the module
59 | module_spec = importlib.util.spec_from_file_location('example_module', fn_path)
60 | # Load the module
61 | example_module = importlib.util.module_from_spec(module_spec)
62 | module_spec.loader.exec_module(example_module)
63 | # Now you can use the module
64 | some_class = getattr(example_module, class_name)
65 | # Now you can create an instance of the class
66 | instance = some_class()
67 | return_dict['result'] = instance.run(file_path)
68 | return_dict['success'] = True
69 | except:
70 | return_dict['traceback'] = trimmed_format_exc()
71 |
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/crazy_functions/ipc_fns/mp.py:
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1 | import platform
2 | import pickle
3 | import multiprocessing
4 |
5 | def run_in_subprocess_wrapper_func(v_args):
6 | func, args, kwargs, return_dict, exception_dict = pickle.loads(v_args)
7 | import sys
8 | try:
9 | result = func(*args, **kwargs)
10 | return_dict['result'] = result
11 | except Exception as e:
12 | exc_info = sys.exc_info()
13 | exception_dict['exception'] = exc_info
14 |
15 | def run_in_subprocess_with_timeout(func, timeout=60):
16 | if platform.system() == 'Linux':
17 | def wrapper(*args, **kwargs):
18 | return_dict = multiprocessing.Manager().dict()
19 | exception_dict = multiprocessing.Manager().dict()
20 | v_args = pickle.dumps((func, args, kwargs, return_dict, exception_dict))
21 | process = multiprocessing.Process(target=run_in_subprocess_wrapper_func, args=(v_args,))
22 | process.start()
23 | process.join(timeout)
24 | if process.is_alive():
25 | process.terminate()
26 | raise TimeoutError(f'功能单元{str(func)}未能在规定时间内完成任务')
27 | process.close()
28 | if 'exception' in exception_dict:
29 | # ooops, the subprocess ran into an exception
30 | exc_info = exception_dict['exception']
31 | raise exc_info[1].with_traceback(exc_info[2])
32 | if 'result' in return_dict.keys():
33 | # If the subprocess ran successfully, return the result
34 | return return_dict['result']
35 | return wrapper
36 | else:
37 | return func
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/crazy_functions/json_fns/select_tool.py:
--------------------------------------------------------------------------------
1 | from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
2 |
3 | def structure_output(txt, prompt, err_msg, run_gpt_fn, pydantic_cls):
4 | gpt_json_io = GptJsonIO(pydantic_cls)
5 | analyze_res = run_gpt_fn(
6 | txt,
7 | sys_prompt=prompt + gpt_json_io.format_instructions
8 | )
9 | try:
10 | friend = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
11 | except JsonStringError as e:
12 | return None, err_msg
13 |
14 | err_msg = ""
15 | return friend, err_msg
16 |
17 |
18 | def select_tool(prompt, run_gpt_fn, pydantic_cls):
19 | pydantic_cls_instance, err_msg = structure_output(
20 | txt=prompt,
21 | prompt="根据提示, 分析应该调用哪个工具函数\n\n",
22 | err_msg=f"不能理解该联系人",
23 | run_gpt_fn=run_gpt_fn,
24 | pydantic_cls=pydantic_cls
25 | )
26 | return pydantic_cls_instance, err_msg
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/crazy_functions/latex_fns/latex_pickle_io.py:
--------------------------------------------------------------------------------
1 | import pickle
2 |
3 |
4 | class SafeUnpickler(pickle.Unpickler):
5 |
6 | def get_safe_classes(self):
7 | from crazy_functions.latex_fns.latex_actions import LatexPaperFileGroup, LatexPaperSplit
8 | from crazy_functions.latex_fns.latex_toolbox import LinkedListNode
9 | from numpy.core.multiarray import scalar
10 | from numpy import dtype
11 | # 定义允许的安全类
12 | safe_classes = {
13 | # 在这里添加其他安全的类
14 | 'LatexPaperFileGroup': LatexPaperFileGroup,
15 | 'LatexPaperSplit': LatexPaperSplit,
16 | 'LinkedListNode': LinkedListNode,
17 | 'scalar': scalar,
18 | 'dtype': dtype,
19 | }
20 | return safe_classes
21 |
22 | def find_class(self, module, name):
23 | # 只允许特定的类进行反序列化
24 | self.safe_classes = self.get_safe_classes()
25 | match_class_name = None
26 | for class_name in self.safe_classes.keys():
27 | if (class_name in f'{module}.{name}'):
28 | match_class_name = class_name
29 | if match_class_name is not None:
30 | return self.safe_classes[match_class_name]
31 | # 如果尝试加载未授权的类，则抛出异常
32 | raise pickle.UnpicklingError(f"Attempted to deserialize unauthorized class '{name}' from module '{module}'")
33 |
34 | def objdump(obj, file="objdump.tmp"):
35 |
36 | with open(file, "wb+") as f:
37 | pickle.dump(obj, f)
38 | return
39 |
40 |
41 | def objload(file="objdump.tmp"):
42 | import os
43 |
44 | if not os.path.exists(file):
45 | return
46 | with open(file, "rb") as f:
47 | unpickler = SafeUnpickler(f)
48 | return unpickler.load()
49 |
--------------------------------------------------------------------------------
/crazy_functions/live_audio/audio_io.py:
--------------------------------------------------------------------------------
1 | import numpy as np
2 | from scipy import interpolate
3 |
4 | def Singleton(cls):
5 | _instance = {}
6 |
7 | def _singleton(*args, **kargs):
8 | if cls not in _instance:
9 | _instance[cls] = cls(*args, **kargs)
10 | return _instance[cls]
11 |
12 | return _singleton
13 |
14 |
15 | @Singleton
16 | class RealtimeAudioDistribution():
17 | def __init__(self) -> None:
18 | self.data = {}
19 | self.max_len = 1024*1024
20 | self.rate = 48000 # 只读，每秒采样数量
21 |
22 | def clean_up(self):
23 | self.data = {}
24 |
25 | def feed(self, uuid, audio):
26 | self.rate, audio_ = audio
27 | # print('feed', len(audio_), audio_[-25:])
28 | if uuid not in self.data:
29 | self.data[uuid] = audio_
30 | else:
31 | new_arr = np.concatenate((self.data[uuid], audio_))
32 | if len(new_arr) > self.max_len: new_arr = new_arr[-self.max_len:]
33 | self.data[uuid] = new_arr
34 |
35 | def read(self, uuid):
36 | if uuid in self.data:
37 | res = self.data.pop(uuid)
38 | # print('\r read-', len(res), '-', max(res), end='', flush=True)
39 | else:
40 | res = None
41 | return res
42 |
43 | def change_sample_rate(audio, old_sr, new_sr):
44 | duration = audio.shape[0] / old_sr
45 |
46 | time_old = np.linspace(0, duration, audio.shape[0])
47 | time_new = np.linspace(0, duration, int(audio.shape[0] * new_sr / old_sr))
48 |
49 | interpolator = interpolate.interp1d(time_old, audio.T)
50 | new_audio = interpolator(time_new).T
51 | return new_audio.astype(np.int16)
--------------------------------------------------------------------------------
/crazy_functions/media_fns/get_media.py:
--------------------------------------------------------------------------------
1 | from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
2 | from shared_utils.docker_as_service_api import stream_daas
3 | from shared_utils.docker_as_service_api import DockerServiceApiComModel
4 | import random
5 |
6 | def download_video(video_id, only_audio, user_name, chatbot, history):
7 | from toolbox import get_log_folder
8 | chatbot.append([None, "Processing..."])
9 | yield from update_ui(chatbot, history)
10 | client_command = f'{video_id} --audio-only' if only_audio else video_id
11 | server_urls = get_conf('DAAS_SERVER_URLS')
12 | server_url = random.choice(server_urls)
13 | docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command)
14 | save_file_dir = get_log_folder(user_name, plugin_name='media_downloader')
15 | for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir):
16 | status_buf = ""
17 | status_buf += "DaaS message: \n\n"
18 | status_buf += output_manifest['server_message'].replace('\n', '<br/>')
19 | status_buf += "\n\n"
20 | status_buf += "DaaS standard error: \n\n"
21 | status_buf += output_manifest['server_std_err'].replace('\n', '<br/>')
22 | status_buf += "\n\n"
23 | status_buf += "DaaS standard output: \n\n"
24 | status_buf += output_manifest['server_std_out'].replace('\n', '<br/>')
25 | status_buf += "\n\n"
26 | status_buf += "DaaS file attach: \n\n"
27 | status_buf += str(output_manifest['server_file_attach'])
28 | yield from update_ui_latest_msg(status_buf, chatbot, history)
29 |
30 | return output_manifest['server_file_attach']
31 |
32 |
33 | def search_videos(keywords):
34 | from toolbox import get_log_folder
35 | client_command = keywords
36 | server_urls = get_conf('DAAS_SERVER_URLS')
37 | server_url = random.choice(server_urls)
38 | server_url = server_url.replace('stream', 'search')
39 | docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command)
40 | save_file_dir = get_log_folder("default_user", plugin_name='media_downloader')
41 | for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir):
42 | return output_manifest['server_message']
43 |
44 |
--------------------------------------------------------------------------------
/crazy_functions/pdf_fns/parse_pdf_grobid.py:
--------------------------------------------------------------------------------
1 | import os
2 | from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages
3 | from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
4 | from toolbox import write_history_to_file, promote_file_to_downloadzone, get_conf, extract_archive
5 | from crazy_functions.pdf_fns.parse_pdf import parse_pdf, translate_pdf
6 |
7 | def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url):
8 | import copy, json
9 | TOKEN_LIMIT_PER_FRAGMENT = 1024
10 | generated_conclusion_files = []
11 | generated_html_files = []
12 | DST_LANG = "中文"
13 | from crazy_functions.pdf_fns.report_gen_html import construct_html
14 | for index, fp in enumerate(file_manifest):
15 | chatbot.append(["当前进度：", f"正在连接GROBID服务，请稍候: {grobid_url}\n如果等待时间过长，请修改config中的GROBID_URL，可修改成本地GROBID服务。"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
16 | article_dict = parse_pdf(fp, grobid_url)
17 | grobid_json_res = os.path.join(get_log_folder(), gen_time_str() + "grobid.json")
18 | with open(grobid_json_res, 'w+', encoding='utf8') as f:
19 | f.write(json.dumps(article_dict, indent=4, ensure_ascii=False))
20 | promote_file_to_downloadzone(grobid_json_res, chatbot=chatbot)
21 | if article_dict is None: raise RuntimeError("解析PDF失败，请检查PDF是否损坏。")
22 | yield from translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG, plugin_kwargs=plugin_kwargs)
23 | chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files)))
24 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
25 |
26 |
27 |
--------------------------------------------------------------------------------
/crazy_functions/pdf_fns/report_gen_html.py:
--------------------------------------------------------------------------------
1 | from toolbox import update_ui, get_conf, trimmed_format_exc, get_log_folder
2 | import os
3 |
4 |
5 |
6 |
7 | class construct_html():
8 | def __init__(self) -> None:
9 | self.html_string = ""
10 |
11 | def add_row(self, a, b):
12 | from toolbox import markdown_convertion
13 | template = """
14 | {
15 | primary_col: {
16 | header: String.raw`__PRIMARY_HEADER__`,
17 | msg: String.raw`__PRIMARY_MSG__`,
18 | },
19 | secondary_rol: {
20 | header: String.raw`__SECONDARY_HEADER__`,
21 | msg: String.raw`__SECONDARY_MSG__`,
22 | }
23 | },
24 | """
25 | def std(str):
26 | str = str.replace(r'`',r'`')
27 | if str.endswith("\\"): str += ' '
28 | if str.endswith("}"): str += ' '
29 | if str.endswith("quot;): str += ' '
30 | return str
31 |
32 | template_ = template
33 | a_lines = a.split('\n')
34 | b_lines = b.split('\n')
35 |
36 | if len(a_lines) == 1 or len(a_lines[0]) > 50:
37 | template_ = template_.replace("__PRIMARY_HEADER__", std(a[:20]))
38 | template_ = template_.replace("__PRIMARY_MSG__", std(markdown_convertion(a)))
39 | else:
40 | template_ = template_.replace("__PRIMARY_HEADER__", std(a_lines[0]))
41 | template_ = template_.replace("__PRIMARY_MSG__", std(markdown_convertion('\n'.join(a_lines[1:]))))
42 |
43 | if len(b_lines) == 1 or len(b_lines[0]) > 50:
44 | template_ = template_.replace("__SECONDARY_HEADER__", std(b[:20]))
45 | template_ = template_.replace("__SECONDARY_MSG__", std(markdown_convertion(b)))
46 | else:
47 | template_ = template_.replace("__SECONDARY_HEADER__", std(b_lines[0]))
48 | template_ = template_.replace("__SECONDARY_MSG__", std(markdown_convertion('\n'.join(b_lines[1:]))))
49 | self.html_string += template_
50 |
51 | def save_file(self, file_name):
52 | from toolbox import get_log_folder
53 | with open('crazy_functions/pdf_fns/report_template.html', 'r', encoding='utf8') as f:
54 | html_template = f.read()
55 | html_template = html_template.replace("__TF_ARR__", self.html_string)
56 | with open(os.path.join(get_log_folder(), file_name), 'w', encoding='utf8') as f:
57 | f.write(html_template.encode('utf-8', 'ignore').decode())
58 | return os.path.join(get_log_folder(), file_name)
59 |
--------------------------------------------------------------------------------
/crazy_functions/pdf_fns/report_template_v2.html:
--------------------------------------------------------------------------------
1 | <!DOCTYPE html>
2 | <html xmlns="http://www.w3.org/1999/xhtml">
3 |
4 | <head>
5 | <meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />
6 | <title>GPT-Academic 翻译报告书</title>
7 | <style>
8 | .centered-a {
9 | color: red;
10 | text-align: center;
11 | margin-bottom: 2%;
12 | font-size: 1.5em;
13 | }
14 | .centered-b {
15 | color: red;
16 | text-align: center;
17 | margin-top: 10%;
18 | margin-bottom: 20%;
19 | font-size: 1.5em;
20 | }
21 | .centered-c {
22 | color: rgba(255, 0, 0, 0);
23 | text-align: center;
24 | margin-top: 2%;
25 | margin-bottom: 20%;
26 | font-size: 7em;
27 | }
28 | </style>
29 | <script>
30 | // Configure MathJax settings
31 | MathJax = {
32 | tex: {
33 | inlineMath: [
34 | ['#39;, '#39;],
35 | ['\(', '\)']
36 | ]
37 | }
38 | }
39 | addEventListener('zero-md-rendered', () => {MathJax.typeset(); console.log('MathJax typeset!');})
40 | </script>
41 | <!-- Load MathJax library -->
42 | <script src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-chtml.js"></script>
43 | <script
44 | type="module"
45 | src="https://cdn.jsdelivr.net/gh/zerodevx/zero-md@2/dist/zero-md.min.js"
46 | ></script>
47 |
48 | </head>
49 |
50 | <body>
51 | <div class="test_temp1" style="width:10%; height: 500px; float:left;">
52 |
53 | </div>
54 | <div class="test_temp2" style="width:80%; height: 500px; float:left;">
55 | <!-- Simply set the `src` attribute to your MD file and win -->
56 | <div class="centered-a">
57 | 请按Ctrl+S保存此页面，否则该页面可能在几分钟后失效。
58 | </div>
59 | <zero-md src="translated_markdown.md" no-shadow>
60 | </zero-md>
61 | <div class="centered-b">
62 | 本报告由GPT-Academic开源项目生成，地址：https://github.com/binary-husky/gpt_academic。
63 | </div>
64 | <div class="centered-c">
65 | 本报告由GPT-Academic开源项目生成，地址：https://github.com/binary-husky/gpt_academic。
66 | </div>
67 | </div>
68 | <div class="test_temp3" style="width:10%; height: 500px; float:left;">
69 | </div>
70 |
71 | </body>
72 |
73 | </html>
--------------------------------------------------------------------------------
/crazy_functions/plugin_template/plugin_class_template.py:
--------------------------------------------------------------------------------
1 | import os, json, base64
2 | from pydantic import BaseModel, Field
3 | from textwrap import dedent
4 | from typing import List
5 |
6 | class ArgProperty(BaseModel): # PLUGIN_ARG_MENU
7 | title: str = Field(description="The title", default="")
8 | description: str = Field(description="The description", default="")
9 | default_value: str = Field(description="The default value", default="")
10 | type: str = Field(description="The type", default="") # currently we support ['string', 'dropdown']
11 | options: List[str] = Field(default=[], description="List of options available for the argument") # only used when type is 'dropdown'
12 |
13 | class GptAcademicPluginTemplate():
14 | def __init__(self):
15 | # please note that `execute` method may run in different threads,
16 | # thus you should not store any state in the plugin instance,
17 | # which may be accessed by multiple threads
18 | pass
19 |
20 |
21 | def define_arg_selection_menu(self):
22 | """
23 | An example as below:
24 | ```
25 | def define_arg_selection_menu(self):
26 | gui_definition = {
27 | "main_input":
28 | ArgProperty(title="main input", description="description", default_value="default_value", type="string").model_dump_json(),
29 | "advanced_arg":
30 | ArgProperty(title="advanced arguments", description="description", default_value="default_value", type="string").model_dump_json(),
31 | "additional_arg_01":
32 | ArgProperty(title="additional", description="description", default_value="default_value", type="string").model_dump_json(),
33 | }
34 | return gui_definition
35 | ```
36 | """
37 | raise NotImplementedError("You need to implement this method in your plugin class")
38 |
39 |
40 | def get_js_code_for_generating_menu(self, btnName):
41 | define_arg_selection = self.define_arg_selection_menu()
42 |
43 | if len(define_arg_selection.keys()) > 8:
44 | raise ValueError("You can only have up to 8 arguments in the define_arg_selection")
45 | # if "main_input" not in define_arg_selection:
46 | # raise ValueError("You must have a 'main_input' in the define_arg_selection")
47 |
48 | DEFINE_ARG_INPUT_INTERFACE = json.dumps(define_arg_selection)
49 | return base64.b64encode(DEFINE_ARG_INPUT_INTERFACE.encode('utf-8')).decode('utf-8')
50 |
51 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
52 | raise NotImplementedError("You need to implement this method in your plugin class")
--------------------------------------------------------------------------------
/crazy_functions/prompts/internet.py:
--------------------------------------------------------------------------------
1 | SearchOptimizerPrompt="""作为一个网页搜索助手，你的任务是结合历史记录，从不同角度，为“原问题”生成个不同版本的“检索词”，从而提高网页检索的精度。生成的问题要求指向对象清晰明确，并与“原问题语言相同”。例如：
2 | 历史记录:
3 | "
4 | Q: 对话背景。
5 | A: 当前对话是关于 Nginx 的介绍和在Ubuntu上的使用等。
6 | "
7 | 原问题: 怎么下载
8 | 检索词: ["Nginx 下载","Ubuntu Nginx","Ubuntu安装Nginx"]
9 | ----------------
10 | 历史记录:
11 | "
12 | Q: 对话背景。
13 | A: 当前对话是关于 Nginx 的介绍和使用等。
14 | Q: 报错 "no connection"
15 | A: 报错"no connection"可能是因为……
16 | "
17 | 原问题: 怎么解决
18 | 检索词: ["Nginx报错"no connection" 解决","Nginx'no connection'报错 原因","Nginx提示'no connection'"]
19 | ----------------
20 | 历史记录:
21 | "
22 |
23 | "
24 | 原问题: 你知道 Python 么？
25 | 检索词: ["Python","Python 使用教程。","Python 特点和优势"]
26 | ----------------
27 | 历史记录:
28 | "
29 | Q: 列出Java的三种特点？
30 | A: 1. Java 是一种编译型语言。
31 | 2. Java 是一种面向对象的编程语言。
32 | 3. Java 是一种跨平台的编程语言。
33 | "
34 | 原问题: 介绍下第2点。
35 | 检索词: ["Java 面向对象特点","Java 面向对象编程优势。","Java 面向对象编程"]
36 | ----------------
37 | 现在有历史记录:
38 | "
39 | {history}
40 | "
41 | 有其原问题: {query}
42 | 直接给出最多{num}个检索词，必须以json形式给出，不得有多余字符:
43 | """
44 |
45 | SearchAcademicOptimizerPrompt="""作为一个学术论文搜索助手，你的任务是结合历史记录，从不同角度，为“原问题”生成个不同版本的“检索词”，从而提高学术论文检索的精度。生成的问题要求指向对象清晰明确，并与“原问题语言相同”。例如：
46 | 历史记录:
47 | "
48 | Q: 对话背景。
49 | A: 当前对话是关于深度学习的介绍和在图像识别中的应用等。
50 | "
51 | 原问题: 怎么下载相关论文
52 | 检索词: ["深度学习 图像识别 论文下载","图像识别 深度学习 研究论文","深度学习 图像识别 论文资源","Deep Learning Image Recognition Paper Download","Image Recognition Deep Learning Research Paper"]
53 | ----------------
54 | 历史记录:
55 | "
56 | Q: 对话背景。
57 | A: 当前对话是关于深度学习的介绍和应用等。
58 | Q: 报错 "模型不收敛"
59 | A: 报错"模型不收敛"可能是因为……
60 | "
61 | 原问题: 怎么解决
62 | 检索词: ["深度学习 模型不收敛 解决方案 论文","深度学习 模型不收敛 原因 研究","深度学习 模型不收敛 论文","Deep Learning Model Convergence Issue Solution Paper","Deep Learning Model Convergence Problem Research"]
63 | ----------------
64 | 历史记录:
65 | "
66 |
67 | "
68 | 原问题: 你知道 GAN 么？
69 | 检索词: ["生成对抗网络 论文","GAN 使用教程 论文","GAN 特点和优势 研究","Generative Adversarial Network Paper","GAN Usage Tutorial Paper"]
70 | ----------------
71 | 历史记录:
72 | "
73 | Q: 列出机器学习的三种应用？
74 | A: 1. 机器学习在图像识别中的应用。
75 | 2. 机器学习在自然语言处理中的应用。
76 | 3. 机器学习在推荐系统中的应用。
77 | "
78 | 原问题: 介绍下第2点。
79 | 检索词: ["机器学习 自然语言处理 应用 论文","机器学习 自然语言处理 研究","机器学习 NLP 应用 论文","Machine Learning Natural Language Processing Application Paper","Machine Learning NLP Research"]
80 | ----------------
81 | 现在有历史记录:
82 | "
83 | {history}
84 | "
85 | 有其原问题: {query}
86 | 直接给出最多{num}个检索词，必须以json形式给出，不得有多余字符:
87 | """
--------------------------------------------------------------------------------
/crazy_functions/rag_fns/rag_file_support.py:
--------------------------------------------------------------------------------
1 | import os
2 | from llama_index.core import SimpleDirectoryReader
3 |
4 | supports_format = ['.csv', '.docx', '.epub', '.ipynb', '.mbox', '.md', '.pdf', '.txt', '.ppt',
5 | '.pptm', '.pptx']
6 |
7 |
8 | # 修改后的 extract_text 函数，结合 SimpleDirectoryReader 和自定义解析逻辑
9 | def extract_text(file_path):
10 | _, ext = os.path.splitext(file_path.lower())
11 |
12 | # 使用 SimpleDirectoryReader 处理它支持的文件格式
13 | if ext in supports_format:
14 | try:
15 | reader = SimpleDirectoryReader(input_files=[file_path])
16 | documents = reader.load_data()
17 | if len(documents) > 0:
18 | return documents[0].text
19 | except Exception as e:
20 | pass
21 |
22 | return None
23 |
--------------------------------------------------------------------------------
/crazy_functions/rag_fns/vector_store_index.py:
--------------------------------------------------------------------------------
1 | from llama_index.core import VectorStoreIndex
2 | from typing import Any, List, Optional
3 |
4 | from llama_index.core.callbacks.base import CallbackManager
5 | from llama_index.core.schema import TransformComponent
6 | from llama_index.core.service_context import ServiceContext
7 | from llama_index.core.settings import (
8 | Settings,
9 | callback_manager_from_settings_or_context,
10 | transformations_from_settings_or_context,
11 | )
12 | from llama_index.core.storage.storage_context import StorageContext
13 |
14 |
15 | class GptacVectorStoreIndex(VectorStoreIndex):
16 |
17 | @classmethod
18 | def default_vector_store(
19 | cls,
20 | storage_context: Optional[StorageContext] = None,
21 | show_progress: bool = False,
22 | callback_manager: Optional[CallbackManager] = None,
23 | transformations: Optional[List[TransformComponent]] = None,
24 | # deprecated
25 | service_context: Optional[ServiceContext] = None,
26 | embed_model = None,
27 | **kwargs: Any,
28 | ):
29 | """Create index from documents.
30 |
31 | Args:
32 | documents (Optional[Sequence[BaseDocument]]): List of documents to
33 | build the index from.
34 |
35 | """
36 | storage_context = storage_context or StorageContext.from_defaults()
37 | docstore = storage_context.docstore
38 | callback_manager = (
39 | callback_manager
40 | or callback_manager_from_settings_or_context(Settings, service_context)
41 | )
42 | transformations = transformations or transformations_from_settings_or_context(
43 | Settings, service_context
44 | )
45 |
46 | with callback_manager.as_trace("index_construction"):
47 |
48 | return cls(
49 | nodes=[],
50 | storage_context=storage_context,
51 | callback_manager=callback_manager,
52 | show_progress=show_progress,
53 | transformations=transformations,
54 | service_context=service_context,
55 | embed_model=embed_model,
56 | **kwargs,
57 | )
58 |
59 |
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/crazy_functions/vector_fns/__init__.py:
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https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/crazy_functions/vector_fns/__init__.py
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/crazy_functions/vector_fns/general_file_loader.py:
--------------------------------------------------------------------------------
1 | # From project chatglm-langchain
2 |
3 |
4 | from langchain.document_loaders import UnstructuredFileLoader
5 | from langchain.text_splitter import CharacterTextSplitter
6 | import re
7 | from typing import List
8 |
9 | class ChineseTextSplitter(CharacterTextSplitter):
10 | def __init__(self, pdf: bool = False, sentence_size: int = None, **kwargs):
11 | super().__init__(**kwargs)
12 | self.pdf = pdf
13 | self.sentence_size = sentence_size
14 |
15 | def split_text1(self, text: str) -> List[str]:
16 | if self.pdf:
17 | text = re.sub(r"\n{3,}", "\n", text)
18 | text = re.sub('\s', ' ', text)
19 | text = text.replace("\n\n", "")
20 | sent_sep_pattern = re.compile('([﹒﹔﹖﹗．。！？]["’”」』]{0,2}|(?=["‘“「『]{1,2}|$))') # del ：；
21 | sent_list = []
22 | for ele in sent_sep_pattern.split(text):
23 | if sent_sep_pattern.match(ele) and sent_list:
24 | sent_list[-1] += ele
25 | elif ele:
26 | sent_list.append(ele)
27 | return sent_list
28 |
29 | def split_text(self, text: str) -> List[str]: ##此处需要进一步优化逻辑
30 | if self.pdf:
31 | text = re.sub(r"\n{3,}", r"\n", text)
32 | text = re.sub('\s', " ", text)
33 | text = re.sub("\n\n", "", text)
34 |
35 | text = re.sub(r'([;；.!?。！？\?])([^”’])', r"\1\n\2", text) # 单字符断句符
36 | text = re.sub(r'(\.{6})([^"’”」』])', r"\1\n\2", text) # 英文省略号
37 | text = re.sub(r'(\…{2})([^"’”」』])', r"\1\n\2", text) # 中文省略号
38 | text = re.sub(r'([;；!?。！？\?]["’”」』]{0,2})([^;；!?，。！？\?])', r'\1\n\2', text)
39 | # 如果双引号前有终止符，那么双引号才是句子的终点，把分句符\n放到双引号后，注意前面的几句都小心保留了双引号
40 | text = text.rstrip() # 段尾如果有多余的\n就去掉它
41 | # 很多规则中会考虑分号;，但是这里我把它忽略不计，破折号、英文双引号等同样忽略，需要的再做些简单调整即可。
42 | ls = [i for i in text.split("\n") if i]
43 | for ele in ls:
44 | if len(ele) > self.sentence_size:
45 | ele1 = re.sub(r'([,，.]["’”」』]{0,2})([^,，.])', r'\1\n\2', ele)
46 | ele1_ls = ele1.split("\n")
47 | for ele_ele1 in ele1_ls:
48 | if len(ele_ele1) > self.sentence_size:
49 | ele_ele2 = re.sub(r'([\n]{1,}| {2,}["’”」』]{0,2})([^\s])', r'\1\n\2', ele_ele1)
50 | ele2_ls = ele_ele2.split("\n")
51 | for ele_ele2 in ele2_ls:
52 | if len(ele_ele2) > self.sentence_size:
53 | ele_ele3 = re.sub('( ["’”」』]{0,2})([^ ])', r'\1\n\2', ele_ele2)
54 | ele2_id = ele2_ls.index(ele_ele2)
55 | ele2_ls = ele2_ls[:ele2_id] + [i for i in ele_ele3.split("\n") if i] + ele2_ls[
56 | ele2_id + 1:]
57 | ele_id = ele1_ls.index(ele_ele1)
58 | ele1_ls = ele1_ls[:ele_id] + [i for i in ele2_ls if i] + ele1_ls[ele_id + 1:]
59 |
60 | id = ls.index(ele)
61 | ls = ls[:id] + [i for i in ele1_ls if i] + ls[id + 1:]
62 | return ls
63 |
64 | def load_file(filepath, sentence_size):
65 | loader = UnstructuredFileLoader(filepath, mode="elements")
66 | textsplitter = ChineseTextSplitter(pdf=False, sentence_size=sentence_size)
67 | docs = loader.load_and_split(text_splitter=textsplitter)
68 | # write_check_file(filepath, docs)
69 | return docs
70 |
71 |
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/crazy_functions/vt_fns/vt_state.py:
--------------------------------------------------------------------------------
1 | import pickle
2 |
3 | class VoidTerminalState():
4 | def __init__(self):
5 | self.reset_state()
6 |
7 | def reset_state(self):
8 | self.has_provided_explanation = False
9 |
10 | def lock_plugin(self, chatbot):
11 | chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'
12 | chatbot._cookies['plugin_state'] = pickle.dumps(self)
13 |
14 | def unlock_plugin(self, chatbot):
15 | self.reset_state()
16 | chatbot._cookies['lock_plugin'] = None
17 | chatbot._cookies['plugin_state'] = pickle.dumps(self)
18 |
19 | def set_state(self, chatbot, key, value):
20 | setattr(self, key, value)
21 | chatbot._cookies['plugin_state'] = pickle.dumps(self)
22 |
23 | def get_state(chatbot):
24 | state = chatbot._cookies.get('plugin_state', None)
25 | if state is not None: state = pickle.loads(state)
26 | else: state = VoidTerminalState()
27 | state.chatbot = chatbot
28 | return state
--------------------------------------------------------------------------------
/crazy_functions/互动小游戏.py:
--------------------------------------------------------------------------------
1 | from toolbox import CatchException, update_ui, update_ui_latest_msg
2 | from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
3 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
4 | from request_llms.bridge_all import predict_no_ui_long_connection
5 | from crazy_functions.game_fns.game_utils import get_code_block, is_same_thing
6 |
7 | @CatchException
8 | def 随机小游戏(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
9 | from crazy_functions.game_fns.game_interactive_story import MiniGame_ResumeStory
10 | # 清空历史
11 | history = []
12 | # 选择游戏
13 | cls = MiniGame_ResumeStory
14 | # 如果之前已经初始化了游戏实例，则继续该实例；否则重新初始化
15 | state = cls.sync_state(chatbot,
16 | llm_kwargs,
17 | cls,
18 | plugin_name='MiniGame_ResumeStory',
19 | callback_fn='crazy_functions.互动小游戏->随机小游戏',
20 | lock_plugin=True
21 | )
22 | yield from state.continue_game(prompt, chatbot, history)
23 |
24 |
25 | @CatchException
26 | def 随机小游戏1(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
27 | from crazy_functions.game_fns.game_ascii_art import MiniGame_ASCII_Art
28 | # 清空历史
29 | history = []
30 | # 选择游戏
31 | cls = MiniGame_ASCII_Art
32 | # 如果之前已经初始化了游戏实例，则继续该实例；否则重新初始化
33 | state = cls.sync_state(chatbot,
34 | llm_kwargs,
35 | cls,
36 | plugin_name='MiniGame_ASCII_Art',
37 | callback_fn='crazy_functions.互动小游戏->随机小游戏1',
38 | lock_plugin=True
39 | )
40 | yield from state.continue_game(prompt, chatbot, history)
41 |
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/crazy_functions/交互功能函数模板.py:
--------------------------------------------------------------------------------
1 | from toolbox import CatchException, update_ui
2 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
3 |
4 | @CatchException
5 | def 交互功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
6 | """
7 | txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
8 | llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
9 | plugin_kwargs 插件模型的参数, 如温度和top_p等, 一般原样传递下去就行
10 | chatbot 聊天显示框的句柄，用于显示给用户
11 | history 聊天历史，前情提要
12 | system_prompt 给gpt的静默提醒
13 | user_request 当前用户的请求信息（IP地址等）
14 | """
15 | history = [] # 清空历史，以免输入溢出
16 | chatbot.append(("这是什么功能？", "交互功能函数模板。在执行完成之后, 可以将自身的状态存储到cookie中, 等待用户的再次调用。"))
17 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
18 |
19 | state = chatbot._cookies.get('plugin_state_0001', None) # 初始化插件状态
20 |
21 | if state is None:
22 | chatbot._cookies['lock_plugin'] = 'crazy_functions.交互功能函数模板->交互功能模板函数' # 赋予插件锁定 锁定插件回调路径，当下一次用户提交时，会直接转到该函数
23 | chatbot._cookies['plugin_state_0001'] = 'wait_user_keyword' # 赋予插件状态
24 |
25 | chatbot.append(("第一次调用：", "请输入关键词, 我将为您查找相关壁纸, 建议使用英文单词, 插件锁定中，请直接提交即可。"))
26 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
27 | return
28 |
29 | if state == 'wait_user_keyword':
30 | chatbot._cookies['lock_plugin'] = None # 解除插件锁定，避免遗忘导致死锁
31 | chatbot._cookies['plugin_state_0001'] = None # 解除插件状态，避免遗忘导致死锁
32 |
33 | # 解除插件锁定
34 | chatbot.append((f"获取关键词：{txt}", ""))
35 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
36 | page_return = get_image_page_by_keyword(txt)
37 | inputs=inputs_show_user=f"Extract all image urls in this html page, pick the first 5 images and show them with markdown format: \n\n {page_return}"
38 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
39 | inputs=inputs, inputs_show_user=inputs_show_user,
40 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
41 | sys_prompt="When you want to show an image, use markdown format. e.g. . If there are no image url provided, answer 'no image url provided'"
42 | )
43 | chatbot[-1] = [chatbot[-1][0], gpt_say]
44 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
45 | return
46 |
47 |
48 |
49 | # ---------------------------------------------------------------------------------
50 |
51 | def get_image_page_by_keyword(keyword):
52 | import requests
53 | from bs4 import BeautifulSoup
54 | response = requests.get(f'https://wallhaven.cc/search?q={keyword}', timeout=2)
55 | res = "image urls: \n"
56 | for image_element in BeautifulSoup(response.content, 'html.parser').findAll("img"):
57 | try:
58 | res += image_element["data-src"]
59 | res += "\n"
60 | except:
61 | pass
62 | return res
63 |
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/crazy_functions/命令行助手.py:
--------------------------------------------------------------------------------
1 | from toolbox import CatchException, update_ui, gen_time_str
2 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
3 | from crazy_functions.crazy_utils import input_clipping
4 | import copy, json
5 |
6 | @CatchException
7 | def 命令行助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
8 | """
9 | txt 输入栏用户输入的文本, 例如需要翻译的一段话, 再例如一个包含了待处理文件的路径
10 | llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
11 | plugin_kwargs 插件模型的参数, 暂时没有用武之地
12 | chatbot 聊天显示框的句柄, 用于显示给用户
13 | history 聊天历史, 前情提要
14 | system_prompt 给gpt的静默提醒
15 | user_request 当前用户的请求信息（IP地址等）
16 | """
17 | # 清空历史, 以免输入溢出
18 | history = []
19 |
20 | # 输入
21 | i_say = "请写bash命令实现以下功能：" + txt
22 | # 开始
23 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
24 | inputs=i_say, inputs_show_user=txt,
25 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
26 | sys_prompt="你是一个Linux大师级用户。注意，当我要求你写bash命令时，尽可能地仅用一行命令解决我的要求。"
27 | )
28 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
29 |
30 |
31 |
32 |
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/crazy_functions/生成函数注释.py:
--------------------------------------------------------------------------------
1 | from loguru import logger
2 | from toolbox import update_ui
3 | from toolbox import CatchException, report_exception
4 | from toolbox import write_history_to_file, promote_file_to_downloadzone
5 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
6 |
7 | def 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
8 | import time, os
9 | logger.info('begin analysis on:', file_manifest)
10 | for index, fp in enumerate(file_manifest):
11 | with open(fp, 'r', encoding='utf-8', errors='replace') as f:
12 | file_content = f.read()
13 |
14 | i_say = f'请对下面的程序文件做一个概述，并对文件中的所有函数生成注释，使用markdown表格输出结果，文件名是{os.path.relpath(fp, project_folder)}，文件内容是 ```{file_content}```'
15 | i_say_show_user = f'[{index+1}/{len(file_manifest)}] 请对下面的程序文件做一个概述，并对文件中的所有函数生成注释: {os.path.abspath(fp)}'
16 | chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
17 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
18 |
19 | msg = '正常'
20 | # ** gpt request **
21 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
22 | i_say, i_say_show_user, llm_kwargs, chatbot, history=[], sys_prompt=system_prompt) # 带超时倒计时
23 |
24 | chatbot[-1] = (i_say_show_user, gpt_say)
25 | history.append(i_say_show_user); history.append(gpt_say)
26 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
27 | time.sleep(2)
28 |
29 | res = write_history_to_file(history)
30 | promote_file_to_downloadzone(res, chatbot=chatbot)
31 | chatbot.append(("完成了吗？", res))
32 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
33 |
34 |
35 |
36 | @CatchException
37 | def 批量生成函数注释(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
38 | history = [] # 清空历史，以免输入溢出
39 | import glob, os
40 | if os.path.exists(txt):
41 | project_folder = txt
42 | else:
43 | if txt == "": txt = '空空如也的输入栏'
44 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
45 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
46 | return
47 | file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.py', recursive=True)] + \
48 | [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)]
49 |
50 | if len(file_manifest) == 0:
51 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
52 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
53 | return
54 | yield from 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
55 |
--------------------------------------------------------------------------------
/crazy_functions/询问多个大语言模型.py:
--------------------------------------------------------------------------------
1 | from toolbox import CatchException, update_ui, get_conf
2 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
3 | import datetime
4 | @CatchException
5 | def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
6 | """
7 | txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
8 | llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行
9 | plugin_kwargs 插件模型的参数，用于灵活调整复杂功能的各种参数
10 | chatbot 聊天显示框的句柄，用于显示给用户
11 | history 聊天历史，前情提要
12 | system_prompt 给gpt的静默提醒
13 | user_request 当前用户的请求信息（IP地址等）
14 | """
15 | history = [] # 清空历史，以免输入溢出
16 | MULTI_QUERY_LLM_MODELS = get_conf('MULTI_QUERY_LLM_MODELS')
17 | chatbot.append((txt, "正在同时咨询" + MULTI_QUERY_LLM_MODELS))
18 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
19 |
20 | # llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
21 | llm_kwargs['llm_model'] = MULTI_QUERY_LLM_MODELS # 支持任意数量的llm接口，用&符号分隔
22 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
23 | inputs=txt, inputs_show_user=txt,
24 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
25 | sys_prompt=system_prompt,
26 | retry_times_at_unknown_error=0
27 | )
28 |
29 | history.append(txt)
30 | history.append(gpt_say)
31 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
32 |
33 |
34 | @CatchException
35 | def 同时问询_指定模型(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
36 | """
37 | txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
38 | llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行
39 | plugin_kwargs 插件模型的参数，用于灵活调整复杂功能的各种参数
40 | chatbot 聊天显示框的句柄，用于显示给用户
41 | history 聊天历史，前情提要
42 | system_prompt 给gpt的静默提醒
43 | user_request 当前用户的请求信息（IP地址等）
44 | """
45 | history = [] # 清空历史，以免输入溢出
46 |
47 | if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
48 | # llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
49 | llm_kwargs['llm_model'] = plugin_kwargs.get("advanced_arg", 'chatglm&gpt-3.5-turbo') # 'chatglm&gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
50 |
51 | chatbot.append((txt, f"正在同时咨询{llm_kwargs['llm_model']}"))
52 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
53 |
54 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
55 | inputs=txt, inputs_show_user=txt,
56 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
57 | sys_prompt=system_prompt,
58 | retry_times_at_unknown_error=0
59 | )
60 |
61 | history.append(txt)
62 | history.append(gpt_say)
63 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
--------------------------------------------------------------------------------
/crazy_functions/读文章写摘要.py:
--------------------------------------------------------------------------------
1 | from toolbox import update_ui
2 | from toolbox import CatchException, report_exception
3 | from toolbox import write_history_to_file, promote_file_to_downloadzone
4 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
5 |
6 |
7 | def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
8 | import time, glob, os
9 | for index, fp in enumerate(file_manifest):
10 | with open(fp, 'r', encoding='utf-8', errors='replace') as f:
11 | file_content = f.read()
12 |
13 | prefix = "接下来请你逐文件分析下面的论文文件，概括其内容" if index==0 else ""
14 | i_say = prefix + f'请对下面的文章片段用中文做一个概述，文件名是{os.path.relpath(fp, project_folder)}，文章内容是 ```{file_content}```'
15 | i_say_show_user = prefix + f'[{index+1}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}'
16 | chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
17 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
18 |
19 | msg = '正常'
20 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, llm_kwargs, chatbot, history=[], sys_prompt=system_prompt) # 带超时倒计时
21 | chatbot[-1] = (i_say_show_user, gpt_say)
22 | history.append(i_say_show_user); history.append(gpt_say)
23 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
24 | time.sleep(2)
25 |
26 | all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)])
27 | i_say = f'根据以上你自己的分析，对全文进行概括，用学术性语言写一段中文摘要，然后再写一段英文摘要（包括{all_file}）。'
28 | chatbot.append((i_say, "[Local Message] waiting gpt response."))
29 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
30 |
31 | msg = '正常'
32 | # ** gpt request **
33 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say, llm_kwargs, chatbot, history=history, sys_prompt=system_prompt) # 带超时倒计时
34 |
35 | chatbot[-1] = (i_say, gpt_say)
36 | history.append(i_say); history.append(gpt_say)
37 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
38 | res = write_history_to_file(history)
39 | promote_file_to_downloadzone(res, chatbot=chatbot)
40 | chatbot.append(("完成了吗？", res))
41 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
42 |
43 |
44 |
45 | @CatchException
46 | def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
47 | history = [] # 清空历史，以免输入溢出
48 | import glob, os
49 | if os.path.exists(txt):
50 | project_folder = txt
51 | else:
52 | if txt == "": txt = '空空如也的输入栏'
53 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
54 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
55 | return
56 | file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] # + \
57 | # [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
58 | # [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
59 | if len(file_manifest) == 0:
60 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
61 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
62 | return
63 | yield from 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
64 |
--------------------------------------------------------------------------------
/crazy_functions/辅助功能.py:
--------------------------------------------------------------------------------
1 | # encoding: utf-8
2 | # @Time : 2023/4/19
3 | # @Author : Spike
4 | # @Descr :
5 | from toolbox import update_ui, get_conf, get_user
6 | from toolbox import CatchException
7 | from toolbox import default_user_name
8 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
9 | import shutil
10 | import os
11 |
12 |
13 | @CatchException
14 | def 猜你想问(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
15 | if txt:
16 | show_say = txt
17 | prompt = txt+'\n回答完问题后，再列出用户可能提出的三个问题。'
18 | else:
19 | prompt = history[-1]+"\n分析上述回答，再列出用户可能提出的三个问题。"
20 | show_say = '分析上述回答，再列出用户可能提出的三个问题。'
21 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
22 | inputs=prompt,
23 | inputs_show_user=show_say,
24 | llm_kwargs=llm_kwargs,
25 | chatbot=chatbot,
26 | history=history,
27 | sys_prompt=system_prompt
28 | )
29 | chatbot[-1] = (show_say, gpt_say)
30 | history.extend([show_say, gpt_say])
31 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
32 |
33 |
34 | @CatchException
35 | def 清除缓存(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
36 | chatbot.append(['清除本地缓存数据', '执行中. 删除数据'])
37 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
38 |
39 | def _get_log_folder(user=default_user_name):
40 | PATH_LOGGING = get_conf('PATH_LOGGING')
41 | _dir = os.path.join(PATH_LOGGING, user)
42 | if not os.path.exists(_dir): os.makedirs(_dir)
43 | return _dir
44 |
45 | def _get_upload_folder(user=default_user_name):
46 | PATH_PRIVATE_UPLOAD = get_conf('PATH_PRIVATE_UPLOAD')
47 | _dir = os.path.join(PATH_PRIVATE_UPLOAD, user)
48 | return _dir
49 |
50 | shutil.rmtree(_get_log_folder(get_user(chatbot)), ignore_errors=True)
51 | shutil.rmtree(_get_upload_folder(get_user(chatbot)), ignore_errors=True)
52 |
53 | chatbot.append(['清除本地缓存数据', '执行完成'])
54 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
--------------------------------------------------------------------------------
/docs/Dockerfile+ChatGLM:
--------------------------------------------------------------------------------
1 | # 此Dockerfile不再维护，请前往docs/GithubAction+ChatGLM+Moss
2 |
--------------------------------------------------------------------------------
/docs/Dockerfile+NoLocal+Latex:
--------------------------------------------------------------------------------
1 | # 此Dockerfile不再维护，请前往docs/GithubAction+NoLocal+Latex
2 |
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/docs/GithubAction+AllCapacity:
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1 | # docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacity --network=host --build-arg http_proxy=http://localhost:10881 --build-arg https_proxy=http://localhost:10881 .
2 |
3 | # 从NVIDIA源，从而支持显卡（检查宿主的nvidia-smi中的cuda版本必须>=11.3）
4 | FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest
5 |
6 | # edge-tts需要的依赖，某些pip包所需的依赖
7 | RUN apt update && apt install ffmpeg build-essential -y
8 | RUN apt-get install -y fontconfig
9 | RUN ln -s /usr/local/texlive/2023/texmf-dist/fonts/truetype /usr/share/fonts/truetype/texlive
10 | RUN fc-cache -fv
11 | RUN apt-get clean
12 |
13 | # use python3 as the system default python
14 | WORKDIR /gpt
15 | RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
16 | # 下载pytorch
17 | RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
18 | # 准备pip依赖
19 | RUN python3 -m pip install openai numpy arxiv rich
20 | RUN python3 -m pip install colorama Markdown pygments pymupdf
21 | RUN python3 -m pip install python-docx moviepy pdfminer
22 | RUN python3 -m pip install zh_langchain==0.2.1 pypinyin
23 | RUN python3 -m pip install rarfile py7zr
24 | RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
25 | # 下载分支
26 | WORKDIR /gpt
27 | RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
28 | WORKDIR /gpt/gpt_academic
29 | RUN git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss
30 |
31 | RUN python3 -m pip install -r requirements.txt
32 | RUN python3 -m pip install -r request_llms/requirements_moss.txt
33 | RUN python3 -m pip install -r request_llms/requirements_qwen.txt
34 | RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
35 | RUN python3 -m pip install -r request_llms/requirements_newbing.txt
36 | RUN python3 -m pip install nougat-ocr
37 | RUN python3 -m pip cache purge
38 |
39 | # 预热Tiktoken模块
40 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
41 |
42 | # 启动
43 | CMD ["python3", "-u", "main.py"]
44 |
--------------------------------------------------------------------------------
/docs/GithubAction+ChatGLM+Moss:
--------------------------------------------------------------------------------
1 |
2 | # 从NVIDIA源，从而支持显卡运损（检查宿主的nvidia-smi中的cuda版本必须>=11.3）
3 | FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
4 | RUN apt-get update
5 | RUN apt-get install -y curl proxychains curl gcc
6 | RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
7 |
8 | # edge-tts需要的依赖，某些pip包所需的依赖
9 | RUN apt update && apt install ffmpeg build-essential -y
10 | RUN apt-get clean
11 |
12 | # use python3 as the system default python
13 | RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
14 | # 下载pytorch
15 | RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
16 | # 下载分支
17 | WORKDIR /gpt
18 | RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
19 | WORKDIR /gpt/gpt_academic
20 | RUN git clone https://github.com/OpenLMLab/MOSS.git request_llms/moss
21 | RUN python3 -m pip install -r requirements.txt
22 | RUN python3 -m pip install -r request_llms/requirements_moss.txt
23 | RUN python3 -m pip install -r request_llms/requirements_qwen.txt
24 | RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
25 | RUN python3 -m pip install -r request_llms/requirements_newbing.txt
26 | RUN python3 -m pip cache purge
27 |
28 |
29 | # 预热Tiktoken模块
30 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
31 |
32 | # 启动
33 | CMD ["python3", "-u", "main.py"]
34 |
--------------------------------------------------------------------------------
/docs/GithubAction+JittorLLMs:
--------------------------------------------------------------------------------
1 | # 从NVIDIA源，从而支持显卡运损（检查宿主的nvidia-smi中的cuda版本必须>=11.3）
2 | FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
3 | ARG useProxyNetwork=''
4 | RUN apt-get update
5 | RUN apt-get install -y curl proxychains curl g++
6 | RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
7 |
8 | # use python3 as the system default python
9 | RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
10 |
11 | # 下载pytorch
12 | RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
13 |
14 | # 下载分支
15 | WORKDIR /gpt
16 | RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
17 | WORKDIR /gpt/gpt_academic
18 | RUN python3 -m pip install -r requirements.txt
19 | RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
20 | RUN python3 -m pip install -r request_llms/requirements_newbing.txt
21 | RUN python3 -m pip install -r request_llms/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I
22 |
23 | # 下载JittorLLMs
24 | RUN git clone https://github.com/binary-husky/JittorLLMs.git --depth 1 request_llms/jittorllms
25 |
26 | # edge-tts需要的依赖
27 | RUN apt update && apt install ffmpeg -y
28 |
29 | # 禁用缓存，确保更新代码
30 | ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache
31 | RUN git pull
32 |
33 | # 预热Tiktoken模块
34 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
35 |
36 | # 启动
37 | CMD ["python3", "-u", "main.py"]
38 |
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/docs/GithubAction+NoLocal:
--------------------------------------------------------------------------------
1 | # 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
2 | # 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal -f docs/Dockerfile+NoLocal .
3 | # 如何运行: docker run --rm -it --net=host gpt-academic-nolocal
4 | FROM python:3.11
5 |
6 | # 指定路径
7 | WORKDIR /gpt
8 |
9 | # 装载项目文件
10 | COPY . .
11 |
12 | # 安装依赖
13 | RUN pip3 install -r requirements.txt
14 |
15 | # edge-tts需要的依赖
16 | RUN apt update && apt install ffmpeg -y
17 |
18 | # 可选步骤，用于预热模块
19 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
20 |
21 | RUN python3 -m pip cache purge && apt-get clean
22 |
23 | # 启动
24 | CMD ["python3", "-u", "main.py"]
25 |
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/docs/GithubAction+NoLocal+AudioAssistant:
--------------------------------------------------------------------------------
1 | # 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
2 | # 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal -f docs/Dockerfile+NoLocal .
3 | # 如何运行: docker run --rm -it --net=host gpt-academic-nolocal
4 | FROM python:3.11
5 |
6 | # 指定路径
7 | WORKDIR /gpt
8 |
9 | # 装载项目文件
10 | COPY . .
11 |
12 | # 安装依赖
13 | RUN pip3 install -r requirements.txt
14 |
15 | # 安装语音插件的额外依赖
16 | RUN pip3 install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
17 |
18 | # edge-tts需要的依赖
19 | RUN apt update && apt install ffmpeg -y
20 |
21 | # 可选步骤，用于预热模块
22 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
23 |
24 | # 启动
25 | CMD ["python3", "-u", "main.py"]
26 |
--------------------------------------------------------------------------------
/docs/GithubAction+NoLocal+Latex:
--------------------------------------------------------------------------------
1 | # 此Dockerfile适用于"无本地模型"的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
2 | # - 1 修改 `config.py`
3 | # - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/GithubAction+NoLocal+Latex .
4 | # - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
5 |
6 | FROM menghuan1918/ubuntu_uv_ctex:latest
7 | ENV DEBIAN_FRONTEND=noninteractive
8 | SHELL ["/bin/bash", "-c"]
9 | WORKDIR /gpt
10 |
11 | # 先复制依赖文件
12 | COPY requirements.txt .
13 |
14 | # 安装依赖
15 | RUN pip install --break-system-packages openai numpy arxiv rich colorama Markdown pygments pymupdf python-docx pdfminer \
16 | && pip install --break-system-packages -r requirements.txt \
17 | && if [ "$(uname -m)" = "x86_64" ]; then \
18 | pip install --break-system-packages nougat-ocr; \
19 | fi \
20 | && pip cache purge \
21 | && rm -rf /root/.cache/pip/*
22 |
23 | # 创建非root用户
24 | RUN useradd -m gptuser && chown -R gptuser /gpt
25 | USER gptuser
26 |
27 | # 最后才复制代码文件,这样代码更新时只需重建最后几层，可以大幅减少docker pull所需的大小
28 | COPY --chown=gptuser:gptuser . .
29 |
30 | # 可选步骤，用于预热模块
31 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
32 |
33 | RUN python3 -m pip cache purge
34 |
35 | # 启动
36 | CMD ["python3", "-u", "main.py"]
37 |
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/docs/GithubAction+NoLocal+Vectordb:
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1 | # 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
2 | # 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal-vs -f docs/GithubAction+NoLocal+Vectordb .
3 | # 如何运行: docker run --rm -it --net=host gpt-academic-nolocal-vs
4 | FROM python:3.11
5 |
6 | # 指定路径
7 | WORKDIR /gpt
8 |
9 | # 装载项目文件
10 | COPY . .
11 |
12 | # 安装依赖
13 | RUN pip3 install -r requirements.txt
14 |
15 | # 安装知识库插件的额外依赖
16 | RUN apt-get update && apt-get install libgl1 -y
17 | RUN pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cpu
18 | RUN pip3 install transformers protobuf langchain sentence-transformers faiss-cpu nltk beautifulsoup4 bitsandbytes tabulate icetk --upgrade
19 | RUN pip3 install unstructured[all-docs] --upgrade
20 | RUN python3 -c 'from check_proxy import warm_up_vectordb; warm_up_vectordb()'
21 |
22 | # edge-tts需要的依赖
23 | RUN apt update && apt install ffmpeg -y
24 |
25 | # 可选步骤，用于预热模块
26 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
27 | RUN python3 -m pip cache purge && apt-get clean
28 |
29 |
30 | # 启动
31 | CMD ["python3", "-u", "main.py"]
32 |
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/docs/WindowsRun.bat:
--------------------------------------------------------------------------------
1 | @echo off
2 | setlocal
3 |
4 | :: 设置环境变量
5 | set ENV_NAME=gpt
6 | set ENV_PATH=%~dp0%ENV_NAME%
7 | set SCRIPT_PATH=%~dp0main.py
8 |
9 | :: 判断环境是否已解压
10 | if not exist "%ENV_PATH%" (
11 | echo Extracting environment...
12 | mkdir "%ENV_PATH%"
13 | tar -xzf gpt.tar.gz -C "%ENV_PATH%"
14 |
15 | :: 运行conda环境激活脚本
16 | call "%ENV_PATH%\Scripts\activate.bat"
17 | ) else (
18 | :: 如果环境已存在,直接激活
19 | call "%ENV_PATH%\Scripts\activate.bat"
20 | )
21 | echo Start to run program:
22 | :: 运行Python脚本
23 | python "%SCRIPT_PATH%"
24 |
25 | endlocal
26 | pause
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/docs/WithFastapi.md:
--------------------------------------------------------------------------------
1 | # Running with fastapi
2 |
3 | We currently support fastapi in order to solve sub-path deploy issue.
4 |
5 | 1. change CUSTOM_PATH setting in `config.py`
6 |
7 | ```sh
8 | nano config.py
9 | ```
10 |
11 | 2. Edit main.py
12 |
13 | ```diff
14 | auto_opentab_delay()
15 | - demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
16 | + demo.queue(concurrency_count=CONCURRENT_COUNT)
17 |
18 | - # 如果需要在二级路径下运行
19 | - # CUSTOM_PATH = get_conf('CUSTOM_PATH')
20 | - # if CUSTOM_PATH != "/":
21 | - # from toolbox import run_gradio_in_subpath
22 | - # run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
23 | - # else:
24 | - # demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
25 |
26 | + 如果需要在二级路径下运行
27 | + CUSTOM_PATH = get_conf('CUSTOM_PATH')
28 | + if CUSTOM_PATH != "/":
29 | + from toolbox import run_gradio_in_subpath
30 | + run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
31 | + else:
32 | + demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
33 |
34 | if __name__ == "__main__":
35 | main()
36 | ```
37 |
38 | 3. Go!
39 |
40 | ```sh
41 | python main.py
42 | ```
43 |
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/docs/demo.jpg:
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https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/docs/demo.jpg
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/docs/demo2.jpg:
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https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/docs/demo2.jpg
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/docs/logo.png:
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https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/docs/logo.png
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/docs/use_audio.md:
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1 | # 使用音频交互功能
2 |
3 |
4 | ## 1. 安装额外依赖
5 | ```
6 | pip install --upgrade pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
7 | ```
8 |
9 | 如果因为特色网络问题导致上述命令无法执行：
10 | 1. git clone alibabacloud-nls-python-sdk这个项目（或者直接前往Github对应网址下载压缩包）.
11 | 命令行输入： `git clone https://github.com/aliyun/alibabacloud-nls-python-sdk.git`
12 | 1. 进入alibabacloud-nls-python-sdk目录命令行输入：`python setup.py install`
13 |
14 |
15 | ## 2. 配置音频功能开关 和 阿里云APPKEY（config.py/config_private.py/环境变量）
16 |
17 | - 注册阿里云账号
18 | - 开通 智能语音交互 （有免费白嫖时长）
19 | - 获取token和appkey
20 | - 未来将逐步用其他更廉价的云服务取代阿里云
21 |
22 | ```
23 | ENABLE_AUDIO = True
24 | ALIYUN_TOKEN = "554a50fcd0bb476c8d07bb630e94d20c" # 此token已经失效
25 | ALIYUN_APPKEY = "RoPlZrM88DnAFkZK" # 此appkey已经失效
26 | ```
27 |
28 | 参考 https://help.aliyun.com/document_detail/450255.html
29 | 先有阿里云开发者账号，登录之后，需要开通 智能语音交互 的功能，可以免费获得一个token，然后在 全部项目 中，创建一个项目，可以获得一个appkey.
30 |
31 | - 进阶功能
32 | 进一步填写ALIYUN_ACCESSKEY和ALIYUN_SECRET实现自动获取ALIYUN_TOKEN
33 | ```
34 | ALIYUN_APPKEY = "RoP1ZrM84DnAFkZK"
35 | ALIYUN_TOKEN = ""
36 | ALIYUN_ACCESSKEY = "LTAI5q6BrFUzoRXVGUWnekh1"
37 | ALIYUN_SECRET = "eHmI20AVWIaQZ0CiTD2bGQVsaP9i68"
38 | ```
39 |
40 |
41 | ## 3.启动
42 |
43 | 启动gpt-academic `python main.py`
44 |
45 | ## 4.点击record from microphe，授权音频采集
46 |
47 | I 如果需要监听自己说话（不监听电脑音频），直接在浏览器中选择对应的麦即可
48 |
49 | II 如果需要监听电脑音频（不监听自己说话），需要安装`VB-Audio VoiceMeeter`，打开声音控制面板(sound control panel)
50 | - 1 `[把电脑的所有外放声音用VoiceMeeter截留]` 在输出区（playback）选项卡，把VoiceMeeter Input虚拟设备set as default设为默认播放设备。
51 | - 2 `[把截留的声音释放到gpt-academic]` 打开gpt-academic主界面，授权音频采集后，在浏览器地址栏或者类似的地方会出现一个麦克风图标，打开后，按照浏览器的提示，选择VoiceMeeter虚拟麦克风。然后刷新页面，重新授权音频采集。
52 | - 3 `[把截留的声音同时释放到耳机或音响]` 完成第一步之后，您应处于听不到电脑声音的状态。为了在截获音频的同时，避免影响正常使用，请完成这最后一步配置。在声音控制面板(sound control panel)输入区（recording）选项卡，把VoiceMeeter Output虚拟设备set as default。双击进入VoiceMeeter Output虚拟设备的设置。
53 | - 3-1 进入VoiceMeeter Output虚拟设备子菜单，打开listen选项卡。
54 | - 3-2 勾选Listen to this device。
55 | - 3-3 在playback through this device下拉菜单中选择你的正常耳机或音响。
56 |
57 | III `[把特殊软件（如腾讯会议）的外放声音用VoiceMeeter截留]` 在完成步骤II的基础上，在特殊软件（如腾讯会议）中，打开声音菜单，选择扬声器VoiceMeeter Input，选择麦克风为正常耳机麦。
58 |
59 | VI 两种音频监听模式切换时，需要刷新页面才有效。
60 |
61 | VII 非localhost运行+非https情况下无法打开录音功能的坑：https://blog.csdn.net/weixin_39461487/article/details/109594434
62 |
63 | ## 5.点击函数插件区“实时音频采集” 或者其他音频交互功能
64 |
--------------------------------------------------------------------------------
/docs/use_tts.md:
--------------------------------------------------------------------------------
1 | # 使用TTS文字转语音
2 |
3 |
4 | ## 1. 使用EDGE-TTS（简单）
5 |
6 | 将本项目配置项修改如下即可
7 |
8 | ```
9 | TTS_TYPE = "EDGE_TTS"
10 | EDGE_TTS_VOICE = "zh-CN-XiaoxiaoNeural"
11 | ```
12 |
13 | ## 2. 使用SoVITS（需要有显卡）
14 |
15 | 使用以下docker-compose.yml文件，先启动SoVITS服务API
16 |
17 | 1. 创建以下文件夹结构
18 | ```shell
19 | .
20 | ├── docker-compose.yml
21 | └── reference
22 | ├── clone_target_txt.txt
23 | └── clone_target_wave.mp3
24 | ```
25 | 2. 其中`docker-compose.yml`为
26 | ```yaml
27 | version: '3.8'
28 | services:
29 | gpt-sovits:
30 | image: fuqingxu/sovits_gptac_trim:latest
31 | container_name: sovits_gptac_container
32 | working_dir: /workspace/gpt_sovits_demo
33 | environment:
34 | - is_half=False
35 | - is_share=False
36 | volumes:
37 | - ./reference:/reference
38 | ports:
39 | - "19880:9880" # 19880 为 sovits api 的暴露端口，记住它
40 | shm_size: 16G
41 | deploy:
42 | resources:
43 | reservations:
44 | devices:
45 | - driver: nvidia
46 | count: "all"
47 | capabilities: [gpu]
48 | command: bash -c "python3 api.py"
49 | ```
50 | 3. 其中`clone_target_wave.mp3`为需要克隆的角色音频，`clone_target_txt.txt`为该音频对应的文字文本（ https://wiki.biligame.com/ys/%E8%A7%92%E8%89%B2%E8%AF%AD%E9%9F%B3 ）
51 | 4. 运行`docker-compose up`
52 | 5. 将本项目配置项修改如下即可
53 | (19880 为 sovits api 的暴露端口，与docker-compose.yml中的端口对应)
54 | ```
55 | TTS_TYPE = "LOCAL_SOVITS_API"
56 | GPT_SOVITS_URL = "http://127.0.0.1:19880"
57 | ```
58 | 6. 启动本项目
--------------------------------------------------------------------------------
/docs/use_vllm.md:
--------------------------------------------------------------------------------
1 | # 使用VLLM
2 |
3 |
4 | ## 1. 首先启动 VLLM，自行选择模型
5 |
6 | ```
7 | python -m vllm.entrypoints.openai.api_server --model /home/hmp/llm/cache/Qwen1___5-32B-Chat --tensor-parallel-size 2 --dtype=half
8 | ```
9 |
10 | 这里使用了存储在 `/home/hmp/llm/cache/Qwen1___5-32B-Chat` 的本地模型，可以根据自己的需求更改。
11 |
12 | ## 2. 测试 VLLM
13 |
14 | ```
15 | curl http://localhost:8000/v1/chat/completions \
16 | -H "Content-Type: application/json" \
17 | -d '{
18 | "model": "/home/hmp/llm/cache/Qwen1___5-32B-Chat",
19 | "messages": [
20 | {"role": "system", "content": "You are a helpful assistant."},
21 | {"role": "user", "content": "怎么实现一个去中心化的控制器?"}
22 | ]
23 | }'
24 | ```
25 |
26 | ## 3. 配置本项目
27 |
28 | ```
29 | API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"
30 | LLM_MODEL = "vllm-/home/hmp/llm/cache/Qwen1___5-32B-Chat(max_token=4096)"
31 | API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "http://localhost:8000/v1/chat/completions"}
32 | ```
33 |
34 | ```
35 | "vllm-/home/hmp/llm/cache/Qwen1___5-32B-Chat(max_token=4096)"
36 | 其中
37 | "vllm-" 是前缀（必要）
38 | "/home/hmp/llm/cache/Qwen1___5-32B-Chat" 是模型名（必要）
39 | "(max_token=6666)" 是配置（非必要）
40 | ```
41 |
42 | ## 4. 启动！
43 |
44 | ```
45 | python main.py
46 | ```
47 |
--------------------------------------------------------------------------------
/request_llms/README.md:
--------------------------------------------------------------------------------
1 | P.S. 如果您按照以下步骤成功接入了新的大模型，欢迎发Pull Requests（如果您在自己接入新模型的过程中遇到困难，欢迎加README底部QQ群联系群主）
2 |
3 |
4 | # 如何接入其他本地大语言模型
5 |
6 | 1. 复制`request_llms/bridge_llama2.py`，重命名为你喜欢的名字
7 |
8 | 2. 修改`load_model_and_tokenizer`方法，加载你的模型和分词器（去该模型官网找demo，复制粘贴即可）
9 |
10 | 3. 修改`llm_stream_generator`方法，定义推理模型（去该模型官网找demo，复制粘贴即可）
11 |
12 | 4. 命令行测试
13 | - 修改`tests/test_llms.py`（聪慧如您，只需要看一眼该文件就明白怎么修改了）
14 | - 运行`python tests/test_llms.py`
15 |
16 | 5. 测试通过后，在`request_llms/bridge_all.py`中做最后的修改，把你的模型完全接入到框架中（聪慧如您，只需要看一眼该文件就明白怎么修改了）
17 |
18 | 6. 修改`LLM_MODEL`配置，然后运行`python main.py`，测试最后的效果
19 |
20 |
21 | # 如何接入其他在线大语言模型
22 |
23 | 1. 复制`request_llms/bridge_zhipu.py`，重命名为你喜欢的名字
24 |
25 | 2. 修改`predict_no_ui_long_connection`
26 |
27 | 3. 修改`predict`
28 |
29 | 4. 命令行测试
30 | - 修改`tests/test_llms.py`（聪慧如您，只需要看一眼该文件就明白怎么修改了）
31 | - 运行`python tests/test_llms.py`
32 |
33 | 5. 测试通过后，在`request_llms/bridge_all.py`中做最后的修改，把你的模型完全接入到框架中（聪慧如您，只需要看一眼该文件就明白怎么修改了）
34 |
35 | 6. 修改`LLM_MODEL`配置，然后运行`python main.py`，测试最后的效果
36 |
--------------------------------------------------------------------------------
/request_llms/bridge_chatglm4.py:
--------------------------------------------------------------------------------
1 | model_name = "ChatGLM4"
2 | cmd_to_install = """
3 | `pip install -r request_llms/requirements_chatglm4.txt`
4 | `pip install modelscope`
5 | `modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat`
6 | """
7 |
8 |
9 | from toolbox import get_conf, ProxyNetworkActivate
10 | from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
11 |
12 |
13 | # ------------------------------------------------------------------------------------------------------------------------
14 | # 🔌💻 Local Model
15 | # ------------------------------------------------------------------------------------------------------------------------
16 | class GetGLM4Handle(LocalLLMHandle):
17 |
18 | def load_model_info(self):
19 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
20 | self.model_name = model_name
21 | self.cmd_to_install = cmd_to_install
22 |
23 | def load_model_and_tokenizer(self):
24 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
25 | import torch
26 | from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer
27 | import os
28 |
29 | LOCAL_MODEL_PATH, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_DEVICE")
30 | model_path = LOCAL_MODEL_PATH
31 | chatglm_tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
32 | chatglm_model = AutoModelForCausalLM.from_pretrained(
33 | model_path,
34 | torch_dtype=torch.bfloat16,
35 | low_cpu_mem_usage=True,
36 | trust_remote_code=True,
37 | device=device
38 | ).eval().to(device)
39 | self._model = chatglm_model
40 | self._tokenizer = chatglm_tokenizer
41 | return self._model, self._tokenizer
42 |
43 |
44 | def llm_stream_generator(self, **kwargs):
45 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
46 | def adaptor(kwargs):
47 | query = kwargs["query"]
48 | max_length = kwargs["max_length"]
49 | top_p = kwargs["top_p"]
50 | temperature = kwargs["temperature"]
51 | history = kwargs["history"]
52 | return query, max_length, top_p, temperature, history
53 |
54 | query, max_length, top_p, temperature, history = adaptor(kwargs)
55 | inputs = self._tokenizer.apply_chat_template([{"role": "user", "content": query}],
56 | add_generation_prompt=True,
57 | tokenize=True,
58 | return_tensors="pt",
59 | return_dict=True
60 | ).to(self._model.device)
61 | gen_kwargs = {"max_length": max_length, "do_sample": True, "top_k": top_p}
62 |
63 | outputs = self._model.generate(**inputs, **gen_kwargs)
64 | outputs = outputs[:, inputs['input_ids'].shape[1]:]
65 | response = self._tokenizer.decode(outputs[0], skip_special_tokens=True)
66 | yield response
67 |
68 | def try_to_import_special_deps(self, **kwargs):
69 | # import something that will raise error if the user does not install requirement_*.txt
70 | # 🏃♂️🏃♂️🏃♂️ 主进程执行
71 | import importlib
72 |
73 | # importlib.import_module('modelscope')
74 |
75 |
76 | # ------------------------------------------------------------------------------------------------------------------------
77 | # 🔌💻 GPT-Academic Interface
78 | # ------------------------------------------------------------------------------------------------------------------------
79 | predict_no_ui_long_connection, predict = get_local_llm_predict_fns(
80 | GetGLM4Handle, model_name, history_format="chatglm3"
81 | )
82 |
--------------------------------------------------------------------------------
/request_llms/bridge_chatglmonnx.py:
--------------------------------------------------------------------------------
1 | model_name = "ChatGLM-ONNX"
2 | cmd_to_install = "`pip install -r request_llms/requirements_chatglm_onnx.txt`"
3 |
4 |
5 | from transformers import AutoModel, AutoTokenizer
6 | import time
7 | import threading
8 | import importlib
9 | from toolbox import update_ui, get_conf
10 | from multiprocessing import Process, Pipe
11 | from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
12 |
13 | from .chatglmoonx import ChatGLMModel, chat_template
14 |
15 |
16 |
17 | # ------------------------------------------------------------------------------------------------------------------------
18 | # 🔌💻 Local Model
19 | # ------------------------------------------------------------------------------------------------------------------------
20 | class GetONNXGLMHandle(LocalLLMHandle):
21 |
22 | def load_model_info(self):
23 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
24 | self.model_name = model_name
25 | self.cmd_to_install = cmd_to_install
26 |
27 | def load_model_and_tokenizer(self):
28 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
29 | import os, glob
30 | if not len(glob.glob("./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/*.bin")) >= 7: # 该模型有七个 bin 文件
31 | from huggingface_hub import snapshot_download
32 | snapshot_download(repo_id="K024/ChatGLM-6b-onnx-u8s8", local_dir="./request_llms/ChatGLM-6b-onnx-u8s8")
33 | def create_model():
34 | return ChatGLMModel(
35 | tokenizer_path = "./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/sentencepiece.model",
36 | onnx_model_path = "./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/chatglm-6b-int8.onnx"
37 | )
38 | self._model = create_model()
39 | return self._model, None
40 |
41 | def llm_stream_generator(self, **kwargs):
42 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
43 | def adaptor(kwargs):
44 | query = kwargs['query']
45 | max_length = kwargs['max_length']
46 | top_p = kwargs['top_p']
47 | temperature = kwargs['temperature']
48 | history = kwargs['history']
49 | return query, max_length, top_p, temperature, history
50 |
51 | query, max_length, top_p, temperature, history = adaptor(kwargs)
52 |
53 | prompt = chat_template(history, query)
54 | for answer in self._model.generate_iterate(
55 | prompt,
56 | max_generated_tokens=max_length,
57 | top_k=1,
58 | top_p=top_p,
59 | temperature=temperature,
60 | ):
61 | yield answer
62 |
63 | def try_to_import_special_deps(self, **kwargs):
64 | # import something that will raise error if the user does not install requirement_*.txt
65 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
66 | pass
67 |
68 |
69 | # ------------------------------------------------------------------------------------------------------------------------
70 | # 🔌💻 GPT-Academic Interface
71 | # ------------------------------------------------------------------------------------------------------------------------
72 | predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetONNXGLMHandle, model_name)
--------------------------------------------------------------------------------
/request_llms/bridge_qwen.py:
--------------------------------------------------------------------------------
1 | import time
2 | import os
3 | from toolbox import update_ui, get_conf, update_ui_latest_msg
4 | from toolbox import check_packages, report_exception, log_chat
5 |
6 | model_name = 'Qwen'
7 |
8 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
9 | observe_window:list=[], console_silence:bool=False):
10 | """
11 | ⭐多线程方法
12 | 函数的说明请见 request_llms/bridge_all.py
13 | """
14 | watch_dog_patience = 5
15 | response = ""
16 |
17 | from .com_qwenapi import QwenRequestInstance
18 | sri = QwenRequestInstance()
19 | for response in sri.generate(inputs, llm_kwargs, history, sys_prompt):
20 | if len(observe_window) >= 1:
21 | observe_window[0] = response
22 | if len(observe_window) >= 2:
23 | if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。")
24 | return response
25 |
26 | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
27 | """
28 | ⭐单线程方法
29 | 函数的说明请见 request_llms/bridge_all.py
30 | """
31 | chatbot.append((inputs, ""))
32 | yield from update_ui(chatbot=chatbot, history=history)
33 |
34 | # 尝试导入依赖，如果缺少依赖，则给出安装建议
35 | try:
36 | check_packages(["dashscope"])
37 | except:
38 | yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade dashscope```。",
39 | chatbot=chatbot, history=history, delay=0)
40 | return
41 |
42 | # 检查DASHSCOPE_API_KEY
43 | if get_conf("DASHSCOPE_API_KEY") == "":
44 | yield from update_ui_latest_msg(f"请配置 DASHSCOPE_API_KEY。",
45 | chatbot=chatbot, history=history, delay=0)
46 | return
47 |
48 | if additional_fn is not None:
49 | from core_functional import handle_core_functionality
50 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
51 | chatbot[-1] = (inputs, "")
52 | yield from update_ui(chatbot=chatbot, history=history)
53 |
54 | # 开始接收回复
55 | from .com_qwenapi import QwenRequestInstance
56 | sri = QwenRequestInstance()
57 | response = f"[Local Message] 等待{model_name}响应中 ..."
58 | for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
59 | chatbot[-1] = (inputs, response)
60 | yield from update_ui(chatbot=chatbot, history=history)
61 |
62 | log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=response)
63 | # 总结输出
64 | if response == f"[Local Message] 等待{model_name}响应中 ...":
65 | response = f"[Local Message] {model_name}响应异常 ..."
66 | history.extend([inputs, response])
67 | yield from update_ui(chatbot=chatbot, history=history)
--------------------------------------------------------------------------------
/request_llms/bridge_qwen_local.py:
--------------------------------------------------------------------------------
1 | model_name = "Qwen_Local"
2 | cmd_to_install = "`pip install -r request_llms/requirements_qwen_local.txt`"
3 |
4 | from toolbox import ProxyNetworkActivate, get_conf
5 | from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
6 |
7 |
8 |
9 | # ------------------------------------------------------------------------------------------------------------------------
10 | # 🔌💻 Local Model
11 | # ------------------------------------------------------------------------------------------------------------------------
12 | class GetQwenLMHandle(LocalLLMHandle):
13 |
14 | def load_model_info(self):
15 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
16 | self.model_name = model_name
17 | self.cmd_to_install = cmd_to_install
18 |
19 | def load_model_and_tokenizer(self):
20 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
21 | # from modelscope import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
22 | from transformers import AutoModelForCausalLM, AutoTokenizer
23 | from transformers.generation import GenerationConfig
24 | with ProxyNetworkActivate('Download_LLM'):
25 | model_id = get_conf('QWEN_LOCAL_MODEL_SELECTION')
26 | self._tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True, resume_download=True)
27 | # use fp16
28 | model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", trust_remote_code=True).eval()
29 | model.generation_config = GenerationConfig.from_pretrained(model_id, trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参
30 | self._model = model
31 |
32 | return self._model, self._tokenizer
33 |
34 | def llm_stream_generator(self, **kwargs):
35 | # 🏃♂️🏃♂️🏃♂️ 子进程执行
36 | def adaptor(kwargs):
37 | query = kwargs['query']
38 | max_length = kwargs['max_length']
39 | top_p = kwargs['top_p']
40 | temperature = kwargs['temperature']
41 | history = kwargs['history']
42 | return query, max_length, top_p, temperature, history
43 |
44 | query, max_length, top_p, temperature, history = adaptor(kwargs)
45 |
46 | for response in self._model.chat_stream(self._tokenizer, query, history=history):
47 | yield response
48 |
49 | def try_to_import_special_deps(self, **kwargs):
50 | # import something that will raise error if the user does not install requirement_*.txt
51 | # 🏃♂️🏃♂️🏃♂️ 主进程执行
52 | import importlib
53 | importlib.import_module('modelscope')
54 |
55 |
56 | # ------------------------------------------------------------------------------------------------------------------------
57 | # 🔌💻 GPT-Academic Interface
58 | # ------------------------------------------------------------------------------------------------------------------------
59 | predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetQwenLMHandle, model_name)
--------------------------------------------------------------------------------
/request_llms/bridge_skylark2.py:
--------------------------------------------------------------------------------
1 | import time
2 | from toolbox import update_ui, get_conf, update_ui_latest_msg
3 | from toolbox import check_packages, report_exception
4 |
5 | model_name = '云雀大模型'
6 |
7 | def validate_key():
8 | YUNQUE_SECRET_KEY = get_conf("YUNQUE_SECRET_KEY")
9 | if YUNQUE_SECRET_KEY == '': return False
10 | return True
11 |
12 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
13 | observe_window:list=[], console_silence:bool=False):
14 | """
15 | ⭐ 多线程方法
16 | 函数的说明请见 request_llms/bridge_all.py
17 | """
18 | watch_dog_patience = 5
19 | response = ""
20 |
21 | if validate_key() is False:
22 | raise RuntimeError('请配置YUNQUE_SECRET_KEY')
23 |
24 | from .com_skylark2api import YUNQUERequestInstance
25 | sri = YUNQUERequestInstance()
26 | for response in sri.generate(inputs, llm_kwargs, history, sys_prompt):
27 | if len(observe_window) >= 1:
28 | observe_window[0] = response
29 | if len(observe_window) >= 2:
30 | if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。")
31 | return response
32 |
33 | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
34 | """
35 | ⭐ 单线程方法
36 | 函数的说明请见 request_llms/bridge_all.py
37 | """
38 | chatbot.append((inputs, ""))
39 | yield from update_ui(chatbot=chatbot, history=history)
40 |
41 | # 尝试导入依赖，如果缺少依赖，则给出安装建议
42 | try:
43 | check_packages(["zhipuai"])
44 | except:
45 | yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。",
46 | chatbot=chatbot, history=history, delay=0)
47 | return
48 |
49 | if validate_key() is False:
50 | yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", chatbot=chatbot, history=history, delay=0)
51 | return
52 |
53 | if additional_fn is not None:
54 | from core_functional import handle_core_functionality
55 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
56 |
57 | # 开始接收回复
58 | from .com_skylark2api import YUNQUERequestInstance
59 | sri = YUNQUERequestInstance()
60 | response = f"[Local Message] 等待{model_name}响应中 ..."
61 | for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
62 | chatbot[-1] = (inputs, response)
63 | yield from update_ui(chatbot=chatbot, history=history)
64 |
65 | # 总结输出
66 | if response == f"[Local Message] 等待{model_name}响应中 ...":
67 | response = f"[Local Message] {model_name}响应异常 ..."
68 | history.extend([inputs, response])
69 | yield from update_ui(chatbot=chatbot, history=history)
--------------------------------------------------------------------------------
/request_llms/bridge_spark.py:
--------------------------------------------------------------------------------
1 |
2 | import time
3 | import threading
4 | import importlib
5 | from toolbox import update_ui, get_conf, update_ui_latest_msg
6 | from multiprocessing import Process, Pipe
7 |
8 | model_name = '星火认知大模型'
9 |
10 | def validate_key():
11 | XFYUN_APPID = get_conf('XFYUN_APPID')
12 | if XFYUN_APPID == '00000000' or XFYUN_APPID == '':
13 | return False
14 | return True
15 |
16 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
17 | observe_window:list=[], console_silence:bool=False):
18 | """
19 | ⭐多线程方法
20 | 函数的说明请见 request_llms/bridge_all.py
21 | """
22 | watch_dog_patience = 5
23 | response = ""
24 |
25 | if validate_key() is False:
26 | raise RuntimeError('请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET')
27 |
28 | from .com_sparkapi import SparkRequestInstance
29 | sri = SparkRequestInstance()
30 | for response in sri.generate(inputs, llm_kwargs, history, sys_prompt, use_image_api=False):
31 | if len(observe_window) >= 1:
32 | observe_window[0] = response
33 | if len(observe_window) >= 2:
34 | if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。")
35 | return response
36 |
37 | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
38 | """
39 | ⭐单线程方法
40 | 函数的说明请见 request_llms/bridge_all.py
41 | """
42 | chatbot.append((inputs, ""))
43 | yield from update_ui(chatbot=chatbot, history=history)
44 |
45 | if validate_key() is False:
46 | yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0)
47 | return
48 |
49 | if additional_fn is not None:
50 | from core_functional import handle_core_functionality
51 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
52 |
53 | # 开始接收回复
54 | from .com_sparkapi import SparkRequestInstance
55 | sri = SparkRequestInstance()
56 | response = f"[Local Message] 等待{model_name}响应中 ..."
57 | for response in sri.generate(inputs, llm_kwargs, history, system_prompt, use_image_api=True):
58 | chatbot[-1] = (inputs, response)
59 | yield from update_ui(chatbot=chatbot, history=history)
60 |
61 | # 总结输出
62 | if response == f"[Local Message] 等待{model_name}响应中 ...":
63 | response = f"[Local Message] {model_name}响应异常 ..."
64 | history.extend([inputs, response])
65 | yield from update_ui(chatbot=chatbot, history=history)
--------------------------------------------------------------------------------
/request_llms/bridge_taichu.py:
--------------------------------------------------------------------------------
1 | import time
2 | import os
3 | from toolbox import update_ui, get_conf, update_ui_latest_msg, log_chat
4 | from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
5 | from toolbox import ChatBotWithCookies
6 |
7 | # model_name = 'Taichu-2.0'
8 | # taichu_default_model = 'taichu_llm'
9 |
10 | def validate_key():
11 | TAICHU_API_KEY = get_conf("TAICHU_API_KEY")
12 | if TAICHU_API_KEY == '': return False
13 | return True
14 |
15 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
16 | observe_window:list=[], console_silence:bool=False):
17 | """
18 | ⭐多线程方法
19 | 函数的说明请见 request_llms/bridge_all.py
20 | """
21 | watch_dog_patience = 5
22 | response = ""
23 |
24 | # if llm_kwargs["llm_model"] == "taichu":
25 | # llm_kwargs["llm_model"] = "taichu"
26 |
27 | if validate_key() is False:
28 | raise RuntimeError('请配置 TAICHU_API_KEY')
29 |
30 | # 开始接收回复
31 | from .com_taichu import TaichuChatInit
32 | zhipu_bro_init = TaichuChatInit()
33 | for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, sys_prompt):
34 | if len(observe_window) >= 1:
35 | observe_window[0] = response
36 | if len(observe_window) >= 2:
37 | if (time.time() - observe_window[1]) > watch_dog_patience:
38 | raise RuntimeError("程序终止。")
39 | return response
40 |
41 |
42 | def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWithCookies,
43 | history:list=[], system_prompt:str='', stream:bool=True, additional_fn:str=None):
44 | """
45 | ⭐单线程方法
46 | 函数的说明请见 request_llms/bridge_all.py
47 | """
48 | chatbot.append([inputs, ""])
49 | yield from update_ui(chatbot=chatbot, history=history)
50 |
51 | if validate_key() is False:
52 | yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
53 | return
54 |
55 | if additional_fn is not None:
56 | from core_functional import handle_core_functionality
57 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
58 | chatbot[-1] = [inputs, ""]
59 | yield from update_ui(chatbot=chatbot, history=history)
60 |
61 | # if llm_kwargs["llm_model"] == "taichu":
62 | # llm_kwargs["llm_model"] = taichu_default_model
63 |
64 | # 开始接收回复
65 | from .com_taichu import TaichuChatInit
66 | zhipu_bro_init = TaichuChatInit()
67 | for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, system_prompt):
68 | chatbot[-1] = [inputs, response]
69 | yield from update_ui(chatbot=chatbot, history=history)
70 | history.extend([inputs, response])
71 | log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=response)
72 | yield from update_ui(chatbot=chatbot, history=history)
--------------------------------------------------------------------------------
/request_llms/com_taichu.py:
--------------------------------------------------------------------------------
1 | # encoding: utf-8
2 | # @Time : 2024/1/22
3 | # @Author : Kilig947 & binary husky
4 | # @Descr : 兼容最新的智谱Ai
5 | from toolbox import get_conf
6 | from toolbox import get_conf, encode_image, get_pictures_list
7 | import requests
8 | import json
9 | class TaichuChatInit:
10 | def __init__(self): ...
11 |
12 | def __conversation_user(self, user_input: str, llm_kwargs:dict):
13 | return {"role": "user", "content": user_input}
14 |
15 | def __conversation_history(self, history:list, llm_kwargs:dict):
16 | messages = []
17 | conversation_cnt = len(history) // 2
18 | if conversation_cnt:
19 | for index in range(0, 2 * conversation_cnt, 2):
20 | what_i_have_asked = self.__conversation_user(history[index], llm_kwargs)
21 | what_gpt_answer = {
22 | "role": "assistant",
23 | "content": history[index + 1]
24 | }
25 | messages.append(what_i_have_asked)
26 | messages.append(what_gpt_answer)
27 | return messages
28 |
29 | def generate_chat(self, inputs:str, llm_kwargs:dict, history:list, system_prompt:str):
30 | TAICHU_API_KEY = get_conf("TAICHU_API_KEY")
31 | params = {
32 | 'api_key': TAICHU_API_KEY,
33 | 'model_code': 'taichu_llm',
34 | 'question': '\n\n'.join(history) + inputs,
35 | 'prefix': system_prompt,
36 | 'temperature': llm_kwargs.get('temperature', 0.95),
37 | 'stream_format': 'json'
38 | }
39 |
40 | api = 'https://ai-maas.wair.ac.cn/maas/v1/model_api/invoke'
41 | response = requests.post(api, json=params, stream=True)
42 | results = ""
43 | if response.status_code == 200:
44 | response.encoding = 'utf-8'
45 | for line in response.iter_lines(decode_unicode=True):
46 | try: delta = json.loads(line)['data']['content']
47 | except: delta = json.loads(line)['choices'][0]['text']
48 | results += delta
49 | yield delta, results
50 | else:
51 | raise ValueError
52 |
53 |
54 | if __name__ == '__main__':
55 | zhipu = TaichuChatInit()
56 | zhipu.generate_chat('你好', {'llm_model': 'glm-4'}, [], '你是WPSAi')
57 |
--------------------------------------------------------------------------------
/request_llms/embed_models/bridge_all_embed.py:
--------------------------------------------------------------------------------
1 | import tiktoken, copy, re
2 | from functools import lru_cache
3 | from concurrent.futures import ThreadPoolExecutor
4 | from toolbox import get_conf, trimmed_format_exc, apply_gpt_academic_string_mask, read_one_api_model_name
5 |
6 | # Endpoint 重定向
7 | API_URL_REDIRECT, AZURE_ENDPOINT, AZURE_ENGINE = get_conf("API_URL_REDIRECT", "AZURE_ENDPOINT", "AZURE_ENGINE")
8 | openai_endpoint = "https://api.openai.com/v1/chat/completions"
9 | if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
10 | azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
11 |
12 |
13 | if openai_endpoint in API_URL_REDIRECT: openai_endpoint = API_URL_REDIRECT[openai_endpoint]
14 |
15 | openai_embed_endpoint = openai_endpoint.replace("chat/completions", "embeddings")
16 |
17 | from .openai_embed import OpenAiEmbeddingModel
18 |
19 | embed_model_info = {
20 | # text-embedding-3-small Increased performance over 2nd generation ada embedding model | 1,536
21 | "text-embedding-3-small": {
22 | "embed_class": OpenAiEmbeddingModel,
23 | "embed_endpoint": openai_embed_endpoint,
24 | "embed_dimension": 1536,
25 | },
26 |
27 | # text-embedding-3-large Most capable embedding model for both english and non-english tasks | 3,072
28 | "text-embedding-3-large": {
29 | "embed_class": OpenAiEmbeddingModel,
30 | "embed_endpoint": openai_embed_endpoint,
31 | "embed_dimension": 3072,
32 | },
33 |
34 | # text-embedding-ada-002 Most capable 2nd generation embedding model, replacing 16 first generation models | 1,536
35 | "text-embedding-ada-002": {
36 | "embed_class": OpenAiEmbeddingModel,
37 | "embed_endpoint": openai_embed_endpoint,
38 | "embed_dimension": 1536,
39 | },
40 | }
41 |
--------------------------------------------------------------------------------
/request_llms/embed_models/openai_embed.py:
--------------------------------------------------------------------------------
1 | from llama_index.embeddings.openai import OpenAIEmbedding
2 | from openai import OpenAI
3 | from toolbox import get_conf
4 | from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder, ProxyNetworkActivate
5 | from shared_utils.key_pattern_manager import select_api_key_for_embed_models
6 | from typing import List, Any
7 |
8 | import numpy as np
9 |
10 | def mean_agg(embeddings):
11 | """Mean aggregation for embeddings."""
12 | return np.array(embeddings).mean(axis=0).tolist()
13 |
14 | class EmbeddingModel():
15 |
16 | def get_agg_embedding_from_queries(
17 | self,
18 | queries: List[str],
19 | agg_fn = None,
20 | ):
21 | """Get aggregated embedding from multiple queries."""
22 | query_embeddings = [self.get_query_embedding(query) for query in queries]
23 | agg_fn = agg_fn or mean_agg
24 | return agg_fn(query_embeddings)
25 |
26 | def get_text_embedding_batch(
27 | self,
28 | texts: List[str],
29 | show_progress: bool = False,
30 | ):
31 | return self.compute_embedding(texts, batch_mode=True)
32 |
33 |
34 | class OpenAiEmbeddingModel(EmbeddingModel):
35 |
36 | def __init__(self, llm_kwargs:dict=None):
37 | self.llm_kwargs = llm_kwargs
38 |
39 | def get_query_embedding(self, query: str):
40 | return self.compute_embedding(query)
41 |
42 | def compute_embedding(self, text="这是要计算嵌入的文本", llm_kwargs:dict=None, batch_mode=False):
43 | from .bridge_all_embed import embed_model_info
44 |
45 | # load kwargs
46 | if llm_kwargs is None:
47 | llm_kwargs = self.llm_kwargs
48 | if llm_kwargs is None:
49 | raise RuntimeError("llm_kwargs is not provided!")
50 |
51 | # setup api and req url
52 | api_key = select_api_key_for_embed_models(llm_kwargs['api_key'], llm_kwargs['embed_model'])
53 | embed_model = llm_kwargs['embed_model']
54 | base_url = embed_model_info[llm_kwargs['embed_model']]['embed_endpoint'].replace('embeddings', '')
55 |
56 | # send and compute
57 | with ProxyNetworkActivate("Connect_OpenAI_Embedding"):
58 | self.oai_client = OpenAI(api_key=api_key, base_url=base_url)
59 | if batch_mode:
60 | input = text
61 | assert isinstance(text, list)
62 | else:
63 | input = [text]
64 | assert isinstance(text, str)
65 | res = self.oai_client.embeddings.create(input=input, model=embed_model)
66 |
67 | # parse result
68 | if batch_mode:
69 | embedding = [d.embedding for d in res.data]
70 | else:
71 | embedding = res.data[0].embedding
72 | return embedding
73 |
74 | def embedding_dimension(self, llm_kwargs=None):
75 | # load kwargs
76 | if llm_kwargs is None:
77 | llm_kwargs = self.llm_kwargs
78 | if llm_kwargs is None:
79 | raise RuntimeError("llm_kwargs is not provided!")
80 |
81 | from .bridge_all_embed import embed_model_info
82 | return embed_model_info[llm_kwargs['embed_model']]['embed_dimension']
83 |
84 | if __name__ == "__main__":
85 | pass
--------------------------------------------------------------------------------
/request_llms/key_manager.py:
--------------------------------------------------------------------------------
1 | import random
2 |
3 | def Singleton(cls):
4 | _instance = {}
5 |
6 | def _singleton(*args, **kargs):
7 | if cls not in _instance:
8 | _instance[cls] = cls(*args, **kargs)
9 | return _instance[cls]
10 |
11 | return _singleton
12 |
13 |
14 | @Singleton
15 | class OpenAI_ApiKeyManager():
16 | def __init__(self, mode='blacklist') -> None:
17 | # self.key_avail_list = []
18 | self.key_black_list = []
19 |
20 | def add_key_to_blacklist(self, key):
21 | self.key_black_list.append(key)
22 |
23 | def select_avail_key(self, key_list):
24 | # select key from key_list, but avoid keys also in self.key_black_list, raise error if no key can be found
25 | available_keys = [key for key in key_list if key not in self.key_black_list]
26 | if not available_keys:
27 | raise KeyError("No available key found.")
28 | selected_key = random.choice(available_keys)
29 | return selected_key
--------------------------------------------------------------------------------
/request_llms/queued_pipe.py:
--------------------------------------------------------------------------------
1 | from multiprocessing import Pipe, Queue
2 | import time
3 | import threading
4 |
5 | class PipeSide(object):
6 | def __init__(self, q_2remote, q_2local) -> None:
7 | self.q_2remote = q_2remote
8 | self.q_2local = q_2local
9 |
10 | def recv(self):
11 | return self.q_2local.get()
12 |
13 | def send(self, buf):
14 | self.q_2remote.put(buf)
15 |
16 | def poll(self):
17 | return not self.q_2local.empty()
18 |
19 | def create_queue_pipe():
20 | q_p2c = Queue()
21 | q_c2p = Queue()
22 | pipe_c = PipeSide(q_2local=q_p2c, q_2remote=q_c2p)
23 | pipe_p = PipeSide(q_2local=q_c2p, q_2remote=q_p2c)
24 | return pipe_c, pipe_p
25 |
--------------------------------------------------------------------------------
/request_llms/requirements_chatglm.txt:
--------------------------------------------------------------------------------
1 | protobuf
2 | cpm_kernels
3 | torch>=1.10
4 | mdtex2html
5 | sentencepiece
6 |
--------------------------------------------------------------------------------
/request_llms/requirements_chatglm4.txt:
--------------------------------------------------------------------------------
1 | protobuf
2 | cpm_kernels
3 | torch>=1.10
4 | transformers>=4.44
5 | mdtex2html
6 | sentencepiece
7 | accelerate
--------------------------------------------------------------------------------
/request_llms/requirements_chatglm_onnx.txt:
--------------------------------------------------------------------------------
1 | protobuf
2 | cpm_kernels
3 | torch>=1.10
4 | mdtex2html
5 | sentencepiece
6 | numpy
7 | onnxruntime
8 | sentencepiece
9 |
--------------------------------------------------------------------------------
/request_llms/requirements_jittorllms.txt:
--------------------------------------------------------------------------------
1 | jittor >= 1.3.7.9
2 | jtorch >= 0.1.3
3 | torch
4 | torchvision
5 | pandas
6 | jieba
7 |
--------------------------------------------------------------------------------
/request_llms/requirements_moss.txt:
--------------------------------------------------------------------------------
1 | torch
2 | sentencepiece
3 | datasets
4 | accelerate
5 | matplotlib
6 | huggingface_hub
7 | triton
8 |
--------------------------------------------------------------------------------
/request_llms/requirements_newbing.txt:
--------------------------------------------------------------------------------
1 | BingImageCreator
2 | certifi
3 | httpx
4 | prompt_toolkit
5 | requests
6 | rich
7 | websockets
8 | httpx[socks]
9 |
--------------------------------------------------------------------------------
/request_llms/requirements_qwen.txt:
--------------------------------------------------------------------------------
1 | dashscope
2 |
--------------------------------------------------------------------------------
/request_llms/requirements_qwen_local.txt:
--------------------------------------------------------------------------------
1 | modelscope
2 | transformers_stream_generator
3 | auto-gptq
4 | optimum
5 | urllib3<2
6 |
--------------------------------------------------------------------------------
/request_llms/requirements_slackclaude.txt:
--------------------------------------------------------------------------------
1 | slack-sdk==3.21.3
2 |
--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | https://public.agent-matrix.com/publish/gradio-3.32.15-py3-none-any.whl
2 | fastapi==0.110
3 | gradio-client==0.8
4 | pypdf2==2.12.1
5 | httpx<=0.25.2
6 | zhipuai==2.0.1
7 | tiktoken>=0.3.3
8 | requests[socks]
9 | pydantic==2.9.2
10 | protobuf==3.20
11 | transformers>=4.27.1,<4.42
12 | scipdf_parser>=0.52
13 | spacy==3.7.4
14 | anthropic>=0.18.1
15 | python-markdown-math
16 | pymdown-extensions>=10.14
17 | websocket-client
18 | beautifulsoup4
19 | prompt_toolkit
20 | latex2mathml
21 | python-docx
22 | mdtex2html
23 | dashscope
24 | pyautogen
25 | colorama
26 | Markdown
27 | pygments
28 | edge-tts>=7.0.0
29 | pymupdf
30 | openai
31 | rjsmin
32 | loguru
33 | arxiv
34 | numpy
35 | rich
36 |
37 |
38 | llama-index-core==0.10.68
39 | llama-index-legacy==0.9.48
40 | llama-index-readers-file==0.1.33
41 | llama-index-readers-llama-parse==0.1.6
42 | llama-index-embeddings-azure-openai==0.1.10
43 | llama-index-embeddings-openai==0.1.10
44 | llama-parse==0.4.9
45 | mdit-py-plugins>=0.3.3
46 | linkify-it-py==2.0.3
--------------------------------------------------------------------------------
/shared_utils/char_visual_effect.py:
--------------------------------------------------------------------------------
1 | def is_full_width_char(ch):
2 | """判断给定的单个字符是否是全角字符"""
3 | if '\u4e00' <= ch <= '\u9fff':
4 | return True # 中文字符
5 | if '\uff01' <= ch <= '\uff5e':
6 | return True # 全角符号
7 | if '\u3000' <= ch <= '\u303f':
8 | return True # CJK标点符号
9 | return False
10 |
11 | def scrolling_visual_effect(text, scroller_max_len):
12 | text = text.\
13 | replace('\n', '').replace('`', '.').replace(' ', '.').replace('<br/>', '.....').replace('#39;, '.')
14 | place_take_cnt = 0
15 | pointer = len(text) - 1
16 |
17 | if len(text) < scroller_max_len:
18 | return text
19 |
20 | while place_take_cnt < scroller_max_len and pointer > 0:
21 | if is_full_width_char(text[pointer]): place_take_cnt += 2
22 | else: place_take_cnt += 1
23 | pointer -= 1
24 |
25 | return text[pointer:]
--------------------------------------------------------------------------------
/shared_utils/colorful.py:
--------------------------------------------------------------------------------
1 | import platform
2 | from sys import stdout
3 | from loguru import logger
4 |
5 | if platform.system()=="Linux":
6 | pass
7 | else:
8 | from colorama import init
9 | init()
10 |
11 | # Do you like the elegance of Chinese characters?
12 | def print红(*kw,**kargs):
13 | print("\033[0;31m",*kw,"\033[0m",**kargs)
14 | def print绿(*kw,**kargs):
15 | print("\033[0;32m",*kw,"\033[0m",**kargs)
16 | def print黄(*kw,**kargs):
17 | print("\033[0;33m",*kw,"\033[0m",**kargs)
18 | def print蓝(*kw,**kargs):
19 | print("\033[0;34m",*kw,"\033[0m",**kargs)
20 | def print紫(*kw,**kargs):
21 | print("\033[0;35m",*kw,"\033[0m",**kargs)
22 | def print靛(*kw,**kargs):
23 | print("\033[0;36m",*kw,"\033[0m",**kargs)
24 |
25 | def print亮红(*kw,**kargs):
26 | print("\033[1;31m",*kw,"\033[0m",**kargs)
27 | def print亮绿(*kw,**kargs):
28 | print("\033[1;32m",*kw,"\033[0m",**kargs)
29 | def print亮黄(*kw,**kargs):
30 | print("\033[1;33m",*kw,"\033[0m",**kargs)
31 | def print亮蓝(*kw,**kargs):
32 | print("\033[1;34m",*kw,"\033[0m",**kargs)
33 | def print亮紫(*kw,**kargs):
34 | print("\033[1;35m",*kw,"\033[0m",**kargs)
35 | def print亮靛(*kw,**kargs):
36 | print("\033[1;36m",*kw,"\033[0m",**kargs)
37 |
38 | # Do you like the elegance of Chinese characters?
39 | def sprint红(*kw):
40 | return "\033[0;31m"+' '.join(kw)+"\033[0m"
41 | def sprint绿(*kw):
42 | return "\033[0;32m"+' '.join(kw)+"\033[0m"
43 | def sprint黄(*kw):
44 | return "\033[0;33m"+' '.join(kw)+"\033[0m"
45 | def sprint蓝(*kw):
46 | return "\033[0;34m"+' '.join(kw)+"\033[0m"
47 | def sprint紫(*kw):
48 | return "\033[0;35m"+' '.join(kw)+"\033[0m"
49 | def sprint靛(*kw):
50 | return "\033[0;36m"+' '.join(kw)+"\033[0m"
51 | def sprint亮红(*kw):
52 | return "\033[1;31m"+' '.join(kw)+"\033[0m"
53 | def sprint亮绿(*kw):
54 | return "\033[1;32m"+' '.join(kw)+"\033[0m"
55 | def sprint亮黄(*kw):
56 | return "\033[1;33m"+' '.join(kw)+"\033[0m"
57 | def sprint亮蓝(*kw):
58 | return "\033[1;34m"+' '.join(kw)+"\033[0m"
59 | def sprint亮紫(*kw):
60 | return "\033[1;35m"+' '.join(kw)+"\033[0m"
61 | def sprint亮靛(*kw):
62 | return "\033[1;36m"+' '.join(kw)+"\033[0m"
63 |
64 | def log红(*kw,**kargs):
65 | logger.opt(depth=1).info(sprint红(*kw))
66 | def log绿(*kw,**kargs):
67 | logger.opt(depth=1).info(sprint绿(*kw))
68 | def log黄(*kw,**kargs):
69 | logger.opt(depth=1).info(sprint黄(*kw))
70 | def log蓝(*kw,**kargs):
71 | logger.opt(depth=1).info(sprint蓝(*kw))
72 | def log紫(*kw,**kargs):
73 | logger.opt(depth=1).info(sprint紫(*kw))
74 | def log靛(*kw,**kargs):
75 | logger.opt(depth=1).info(sprint靛(*kw))
76 |
77 | def log亮红(*kw,**kargs):
78 | logger.opt(depth=1).info(sprint亮红(*kw))
79 | def log亮绿(*kw,**kargs):
80 | logger.opt(depth=1).info(sprint亮绿(*kw))
81 | def log亮黄(*kw,**kargs):
82 | logger.opt(depth=1).info(sprint亮黄(*kw))
83 | def log亮蓝(*kw,**kargs):
84 | logger.opt(depth=1).info(sprint亮蓝(*kw))
85 | def log亮紫(*kw,**kargs):
86 | logger.opt(depth=1).info(sprint亮紫(*kw))
87 | def log亮靛(*kw,**kargs):
88 | logger.opt(depth=1).info(sprint亮靛(*kw))
--------------------------------------------------------------------------------
/shared_utils/connect_void_terminal.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | """
4 | =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
5 | 接驳void-terminal:
6 | - set_conf: 在运行过程中动态地修改配置
7 | - set_multi_conf: 在运行过程中动态地修改多个配置
8 | - get_plugin_handle: 获取插件的句柄
9 | - get_plugin_default_kwargs: 获取插件的默认参数
10 | - get_chat_handle: 获取简单聊天的句柄
11 | - get_chat_default_kwargs: 获取简单聊天的默认参数
12 | =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
13 | """
14 |
15 |
16 | def get_plugin_handle(plugin_name):
17 | """
18 | e.g. plugin_name = 'crazy_functions.Markdown_Translate->Markdown翻译指定语言'
19 | """
20 | import importlib
21 |
22 | assert (
23 | "->" in plugin_name
24 | ), "Example of plugin_name: crazy_functions.Markdown_Translate->Markdown翻译指定语言"
25 | module, fn_name = plugin_name.split("->")
26 | f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name)
27 | return f_hot_reload
28 |
29 |
30 | def get_chat_handle():
31 | """
32 | Get chat function
33 | """
34 | from request_llms.bridge_all import predict_no_ui_long_connection
35 |
36 | return predict_no_ui_long_connection
37 |
38 |
39 | def get_plugin_default_kwargs():
40 | """
41 | Get Plugin Default Arguments
42 | """
43 | from toolbox import ChatBotWithCookies, load_chat_cookies
44 |
45 | cookies = load_chat_cookies()
46 | llm_kwargs = {
47 | "api_key": cookies["api_key"],
48 | "llm_model": cookies["llm_model"],
49 | "top_p": 1.0,
50 | "max_length": None,
51 | "temperature": 1.0,
52 | }
53 | chatbot = ChatBotWithCookies(llm_kwargs)
54 |
55 | # txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request
56 | DEFAULT_FN_GROUPS_kwargs = {
57 | "main_input": "./README.md",
58 | "llm_kwargs": llm_kwargs,
59 | "plugin_kwargs": {},
60 | "chatbot_with_cookie": chatbot,
61 | "history": [],
62 | "system_prompt": "You are a good AI.",
63 | "user_request": None,
64 | }
65 | return DEFAULT_FN_GROUPS_kwargs
66 |
67 |
68 | def get_chat_default_kwargs():
69 | """
70 | Get Chat Default Arguments
71 | """
72 | from toolbox import load_chat_cookies
73 |
74 | cookies = load_chat_cookies()
75 | llm_kwargs = {
76 | "api_key": cookies["api_key"],
77 | "llm_model": cookies["llm_model"],
78 | "top_p": 1.0,
79 | "max_length": None,
80 | "temperature": 1.0,
81 | }
82 | default_chat_kwargs = {
83 | "inputs": "Hello there, are you ready?",
84 | "llm_kwargs": llm_kwargs,
85 | "history": [],
86 | "sys_prompt": "You are AI assistant",
87 | "observe_window": None,
88 | "console_silence": False,
89 | }
90 |
91 | return default_chat_kwargs
92 |
--------------------------------------------------------------------------------
/shared_utils/logging.py:
--------------------------------------------------------------------------------
1 | from loguru import logger
2 | import logging
3 | import sys
4 | import os
5 |
6 | def chat_log_filter(record):
7 | return "chat_msg" in record["extra"]
8 |
9 | def not_chat_log_filter(record):
10 | return "chat_msg" not in record["extra"]
11 |
12 | def formatter_with_clip(record):
13 | # Note this function returns the string to be formatted, not the actual message to be logged
14 | # record["extra"]["serialized"] = "555555"
15 | max_len = 12
16 | record['function_x'] = record['function'].center(max_len)
17 | if len(record['function_x']) > max_len:
18 | record['function_x'] = ".." + record['function_x'][-(max_len-2):]
19 | record['line_x'] = str(record['line']).ljust(3)
20 | return '<green>{time:HH:mm}</green> | <cyan>{function_x}</cyan>:<cyan>{line_x}</cyan> | <level>{message}</level>\n'
21 |
22 | def setup_logging(PATH_LOGGING):
23 |
24 | admin_log_path = os.path.join(PATH_LOGGING, "admin")
25 | os.makedirs(admin_log_path, exist_ok=True)
26 | sensitive_log_path = os.path.join(admin_log_path, "chat_secrets.log")
27 | regular_log_path = os.path.join(admin_log_path, "console_log.log")
28 | logger.remove()
29 | logger.configure(
30 | levels=[dict(name="WARNING", color="<g>")],
31 | )
32 |
33 | logger.add(
34 | sys.stderr,
35 | format=formatter_with_clip,
36 | # format='<green>{time:HH:mm}</green> | <cyan>{function}</cyan>:<cyan>{line}</cyan> - <level>{message}</level>',
37 | filter=(lambda record: not chat_log_filter(record)),
38 | colorize=True,
39 | enqueue=True
40 | )
41 |
42 | logger.add(
43 | sensitive_log_path,
44 | format='<green>{time:MM-DD HH:mm:ss}</green> | <level>{level: <8}</level> | <cyan>{name}</cyan>:<cyan>{function}</cyan>:<cyan>{line}</cyan> - <level>{message}</level>',
45 | rotation="10 MB",
46 | filter=chat_log_filter,
47 | enqueue=True,
48 | )
49 |
50 | logger.add(
51 | regular_log_path,
52 | format='<green>{time:MM-DD HH:mm:ss}</green> | <level>{level: <8}</level> | <cyan>{name}</cyan>:<cyan>{function}</cyan>:<cyan>{line}</cyan> - <level>{message}</level>',
53 | rotation="10 MB",
54 | filter=not_chat_log_filter,
55 | enqueue=True,
56 | )
57 |
58 | logging.getLogger("httpx").setLevel(logging.WARNING)
59 |
60 | logger.warning(f"所有对话记录将自动保存在本地目录{sensitive_log_path}, 请注意自我隐私保护哦！")
61 |
62 |
63 | # logger.bind(chat_msg=True).info("This message is logged to the file!")
64 | # logger.debug(f"debug message")
65 | # logger.info(f"info message")
66 | # logger.success(f"success message")
67 | # logger.error(f"error message")
68 | # logger.add("special.log", filter=lambda record: "special" in record["extra"])
69 | # logger.debug("This message is not logged to the file")
70 |
--------------------------------------------------------------------------------
/shared_utils/map_names.py:
--------------------------------------------------------------------------------
1 | import re
2 | mapping_dic = {
3 | # "qianfan": "qianfan（文心一言大模型）",
4 | # "zhipuai": "zhipuai（智谱GLM4超级模型🔥）",
5 | # "gpt-4-1106-preview": "gpt-4-1106-preview（新调优版本GPT-4🔥）",
6 | # "gpt-4-vision-preview": "gpt-4-vision-preview（识图模型GPT-4V）",
7 | }
8 |
9 | rev_mapping_dic = {}
10 | for k, v in mapping_dic.items():
11 | rev_mapping_dic[v] = k
12 |
13 | def map_model_to_friendly_names(m):
14 | if m in mapping_dic:
15 | return mapping_dic[m]
16 | return m
17 |
18 | def map_friendly_names_to_model(m):
19 | if m in rev_mapping_dic:
20 | return rev_mapping_dic[m]
21 | return m
22 |
23 | def read_one_api_model_name(model: str):
24 | """return real model name and max_token.
25 | """
26 | max_token_pattern = r"\(max_token=(\d+)\)"
27 | match = re.search(max_token_pattern, model)
28 | if match:
29 | max_token_tmp = match.group(1) # 获取 max_token 的值
30 | max_token_tmp = int(max_token_tmp)
31 | model = re.sub(max_token_pattern, "", model) # 从原字符串中删除 "(max_token=...)"
32 | else:
33 | max_token_tmp = 4096
34 | return model, max_token_tmp
--------------------------------------------------------------------------------
/tests/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/tests/__init__.py
--------------------------------------------------------------------------------
/tests/init_test.py:
--------------------------------------------------------------------------------
1 | def validate_path():
2 | import os, sys
3 |
4 | os.path.dirname(__file__)
5 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..")
6 | os.chdir(root_dir_assume)
7 | sys.path.append(root_dir_assume)
8 |
9 |
10 | validate_path() # validate path so you can run from base directory
11 |
--------------------------------------------------------------------------------
/tests/test_anim_gen.py:
--------------------------------------------------------------------------------
1 | """
2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
3 | """
4 |
5 | import init_test
6 | import os, sys
7 |
8 |
9 | if __name__ == "__main__":
10 | from test_utils import plugin_test
11 |
12 | plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A point moving along function culve y=sin(x), starting from x=0 and stop at x=4*\pi.")
13 |
--------------------------------------------------------------------------------
/tests/test_bilibili_down.py:
--------------------------------------------------------------------------------
1 | """
2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
3 | """
4 |
5 | import init_test
6 | import os, sys
7 |
8 | if __name__ == "__main__":
9 | from experimental_mods.get_bilibili_resource import download_bilibili
10 | download_bilibili("BV1LSSHYXEtv", only_audio=True, user_name="test")
11 |
12 | # if __name__ == "__main__":
13 | # from test_utils import plugin_test
14 |
15 | # plugin_test(plugin='crazy_functions.VideoResource_GPT->视频任务', main_input="帮我找到《天文馆的猫》，歌手泠鸢")
16 |
--------------------------------------------------------------------------------
/tests/test_doc2x.py:
--------------------------------------------------------------------------------
1 | import init_test
2 |
3 | from crazy_functions.pdf_fns.parse_pdf_via_doc2x import 解析PDF_DOC2X_转Latex
4 |
5 | # 解析PDF_DOC2X_转Latex("gpt_log/arxiv_cache_old/2410.10819/workfolder/merge.pdf")
6 | # 解析PDF_DOC2X_转Latex("gpt_log/arxiv_cache_ooo/2410.07095/workfolder/merge.pdf")
7 | 解析PDF_DOC2X_转Latex("2410.11190v2.pdf")
8 |
--------------------------------------------------------------------------------
/tests/test_key_pattern_manager.py:
--------------------------------------------------------------------------------
1 | import unittest
2 |
3 | def validate_path():
4 | import os, sys
5 |
6 | os.path.dirname(__file__)
7 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..")
8 | os.chdir(root_dir_assume)
9 | sys.path.append(root_dir_assume)
10 |
11 |
12 | validate_path() # validate path so you can run from base directory
13 |
14 | from shared_utils.key_pattern_manager import is_openai_api_key
15 |
16 | class TestKeyPatternManager(unittest.TestCase):
17 | def test_is_openai_api_key_with_valid_key(self):
18 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
19 | self.assertTrue(is_openai_api_key(key))
20 |
21 | key = "sx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
22 | self.assertFalse(is_openai_api_key(key))
23 |
24 | key = "sess-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
25 | self.assertTrue(is_openai_api_key(key))
26 |
27 | key = "sess-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
28 | self.assertFalse(is_openai_api_key(key))
29 |
30 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxxxxxxxxxxxxxxxxxxx"
31 | self.assertTrue(is_openai_api_key(key))
32 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxxxxxxxxxxxxxxxx"
33 | self.assertTrue(is_openai_api_key(key))
34 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxx-xxxxxxxxxxxxx"
35 | self.assertTrue(is_openai_api_key(key))
36 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxxxxxxxxxxxxxx"
37 | self.assertFalse(is_openai_api_key(key))
38 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxxxxxxxxxxxxxxxxx"
39 | self.assertFalse(is_openai_api_key(key))
40 |
41 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxxxxxxxxxxx-xxxxxxxx"
42 | self.assertTrue(is_openai_api_key(key))
43 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxxxxx-xxxxxxxx"
44 | self.assertTrue(is_openai_api_key(key))
45 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxxxxxxx"
46 | self.assertFalse(is_openai_api_key(key))
47 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxxxxxxxxxxxx"
48 | self.assertFalse(is_openai_api_key(key))
49 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxx啊xxxxxxx"
50 | self.assertFalse(is_openai_api_key(key))
51 |
52 |
53 | def test_is_openai_api_key_with_invalid_key(self):
54 | key = "invalid_key"
55 | self.assertFalse(is_openai_api_key(key))
56 |
57 | def test_is_openai_api_key_with_custom_pattern(self):
58 | # Assuming you have set a custom pattern in your configuration
59 | key = "custom-pattern-key"
60 | self.assertFalse(is_openai_api_key(key))
61 |
62 | if __name__ == '__main__':
63 | unittest.main()
--------------------------------------------------------------------------------
/tests/test_latex_auto_correct.py:
--------------------------------------------------------------------------------
1 | """
2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
3 | """
4 |
5 |
6 | import os, sys, importlib
7 |
8 |
9 | def validate_path():
10 | dir_name = os.path.dirname(__file__)
11 | root_dir_assume = os.path.abspath(dir_name + "/..")
12 | os.chdir(root_dir_assume)
13 | sys.path.append(root_dir_assume)
14 |
15 |
16 | validate_path() # 返回项目根路径
17 |
18 | if __name__ == "__main__":
19 | plugin_test = importlib.import_module('test_utils').plugin_test
20 |
21 |
22 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2203.01927")
23 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/arxiv_cache/2203.01927/workfolder")
24 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2410.05779")
25 | plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/default_user/workfolder")
26 |
27 |
--------------------------------------------------------------------------------
/tests/test_llms.py:
--------------------------------------------------------------------------------
1 | # """
2 | # 对各个llm模型进行单元测试
3 | # """
4 | def validate_path():
5 | import os, sys
6 |
7 | os.path.dirname(__file__)
8 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..")
9 | os.chdir(root_dir_assume)
10 | sys.path.append(root_dir_assume)
11 |
12 |
13 | validate_path() # validate path so you can run from base directory
14 |
15 | if "在线模型":
16 | if __name__ == "__main__":
17 | from request_llms.bridge_taichu import predict_no_ui_long_connection
18 | # from request_llms.bridge_cohere import predict_no_ui_long_connection
19 | # from request_llms.bridge_spark import predict_no_ui_long_connection
20 | # from request_llms.bridge_zhipu import predict_no_ui_long_connection
21 | # from request_llms.bridge_chatglm3 import predict_no_ui_long_connection
22 | llm_kwargs = {
23 | "llm_model": "taichu",
24 | "max_length": 4096,
25 | "top_p": 1,
26 | "temperature": 1,
27 | }
28 |
29 | result = predict_no_ui_long_connection(
30 | inputs="请问什么是质子？", llm_kwargs=llm_kwargs, history=["你好", "我好！"], sys_prompt="系统"
31 | )
32 | print("final result:", result)
33 | print("final result:", result)
34 |
35 |
36 | if "本地模型":
37 | if __name__ == "__main__":
38 | # from request_llms.bridge_newbingfree import predict_no_ui_long_connection
39 | # from request_llms.bridge_moss import predict_no_ui_long_connection
40 | # from request_llms.bridge_jittorllms_pangualpha import predict_no_ui_long_connection
41 | # from request_llms.bridge_jittorllms_llama import predict_no_ui_long_connection
42 | # from request_llms.bridge_claude import predict_no_ui_long_connection
43 | # from request_llms.bridge_internlm import predict_no_ui_long_connection
44 | # from request_llms.bridge_deepseekcoder import predict_no_ui_long_connection
45 | # from request_llms.bridge_qwen_7B import predict_no_ui_long_connection
46 | # from request_llms.bridge_qwen_local import predict_no_ui_long_connection
47 | llm_kwargs = {
48 | "max_length": 4096,
49 | "top_p": 1,
50 | "temperature": 1,
51 | }
52 | result = predict_no_ui_long_connection(
53 | inputs="请问什么是质子？", llm_kwargs=llm_kwargs, history=["你好", "我好！"], sys_prompt=""
54 | )
55 | print("final result:", result)
56 |
57 |
--------------------------------------------------------------------------------
/tests/test_media.py:
--------------------------------------------------------------------------------
1 | """
2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
3 | """
4 |
5 | import init_test
6 | import os, sys
7 |
8 |
9 | if __name__ == "__main__":
10 | from test_utils import plugin_test
11 |
12 | plugin_test(plugin='crazy_functions.VideoResource_GPT->多媒体任务', main_input="我想找一首歌，里面有句歌词是“turn your face towards the sun”")
13 |
14 | # plugin_test(plugin='crazy_functions.Internet_GPT->连接网络回答问题', main_input="谁是应急食品？")
15 |
16 | # plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"})
17 |
18 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2307.07522")
19 |
20 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='build/pdf/t1.pdf')
21 |
22 | # plugin_test(
23 | # plugin="crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF",
24 | # main_input="G:/SEAFILE_LOCAL/50503047/我的资料库/学位/paperlatex/aaai/Fu_8368_with_appendix",
25 | # )
26 |
27 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep')
28 |
29 | # plugin_test(plugin='crazy_functions.批量翻译PDF文档_NOUGAT->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
30 |
31 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件，对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析')
32 |
33 | # plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表')
34 |
35 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个Python项目', main_input="crazy_functions/test_project/python/dqn")
36 |
37 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个C项目', main_input="crazy_functions/test_project/cpp/cppipc")
38 |
39 | # plugin_test(plugin='crazy_functions.Latex_Project_Polish->Latex英文润色', main_input="crazy_functions/test_project/latex/attention")
40 |
41 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown中译英', main_input="README.md")
42 |
43 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
44 |
45 | # plugin_test(plugin='crazy_functions.谷歌检索小助手->谷歌检索小助手', main_input="https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=auto+reinforcement+learning&btnG=")
46 |
47 | # plugin_test(plugin='crazy_functions.总结word文档->总结word文档', main_input="crazy_functions/test_project/pdf_and_word")
48 |
49 | # plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
50 |
51 | # plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
52 |
53 | # plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")
54 |
55 | # for lang in ["English", "French", "Japanese", "Korean", "Russian", "Italian", "German", "Portuguese", "Arabic"]:
56 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown翻译指定语言', main_input="README.md", advanced_arg={"advanced_arg": lang})
57 |
58 | # plugin_test(plugin='crazy_functions.知识库文件注入->知识库文件注入', main_input="./")
59 |
60 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="What is the installation method？")
61 |
62 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="远程云服务器部署？")
63 |
64 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2210.03629")
65 |
66 |
--------------------------------------------------------------------------------
/tests/test_plugins.py:
--------------------------------------------------------------------------------
1 | """
2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
3 | """
4 |
5 | import init_test
6 | import os, sys
7 |
8 |
9 | if __name__ == "__main__":
10 | from test_utils import plugin_test
11 |
12 | plugin_test(plugin='crazy_functions.SourceCode_Comment->注释Python项目', main_input="build/test/python_comment")
13 |
14 | # plugin_test(plugin='crazy_functions.Internet_GPT->连接网络回答问题', main_input="谁是应急食品？")
15 |
16 | # plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"})
17 |
18 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2307.07522")
19 |
20 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='build/pdf/t1.pdf')
21 |
22 | # plugin_test(
23 | # plugin="crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF",
24 | # main_input="G:/SEAFILE_LOCAL/50503047/我的资料库/学位/paperlatex/aaai/Fu_8368_with_appendix",
25 | # )
26 |
27 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep')
28 |
29 | # plugin_test(plugin='crazy_functions.批量翻译PDF文档_NOUGAT->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
30 |
31 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件，对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析')
32 |
33 | # plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表')
34 |
35 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个Python项目', main_input="crazy_functions/test_project/python/dqn")
36 |
37 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个C项目', main_input="crazy_functions/test_project/cpp/cppipc")
38 |
39 | # plugin_test(plugin='crazy_functions.Latex_Project_Polish->Latex英文润色', main_input="crazy_functions/test_project/latex/attention")
40 |
41 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown中译英', main_input="README.md")
42 |
43 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
44 |
45 | # plugin_test(plugin='crazy_functions.谷歌检索小助手->谷歌检索小助手', main_input="https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=auto+reinforcement+learning&btnG=")
46 |
47 | # plugin_test(plugin='crazy_functions.总结word文档->总结word文档', main_input="crazy_functions/test_project/pdf_and_word")
48 |
49 | # plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
50 |
51 | # plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
52 |
53 | # plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")
54 |
55 | # for lang in ["English", "French", "Japanese", "Korean", "Russian", "Italian", "German", "Portuguese", "Arabic"]:
56 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown翻译指定语言', main_input="README.md", advanced_arg={"advanced_arg": lang})
57 |
58 | # plugin_test(plugin='crazy_functions.知识库文件注入->知识库文件注入', main_input="./")
59 |
60 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="What is the installation method？")
61 |
62 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="远程云服务器部署？")
63 |
64 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2210.03629")
65 |
66 |
--------------------------------------------------------------------------------
/tests/test_rag.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/tests/test_rag.py
--------------------------------------------------------------------------------
/tests/test_safe_pickle.py:
--------------------------------------------------------------------------------
1 | def validate_path():
2 | import os, sys
3 | os.path.dirname(__file__)
4 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..")
5 | os.chdir(root_dir_assume)
6 | sys.path.append(root_dir_assume)
7 | validate_path() # validate path so you can run from base directory
8 |
9 | from crazy_functions.latex_fns.latex_pickle_io import objdump, objload
10 | from crazy_functions.latex_fns.latex_actions import LatexPaperFileGroup, LatexPaperSplit
11 | pfg = LatexPaperFileGroup()
12 | pfg.get_token_num = None
13 | pfg.target = "target_elem"
14 | x = objdump(pfg)
15 | t = objload()
16 |
17 | print(t.target)
--------------------------------------------------------------------------------
/tests/test_searxng.py:
--------------------------------------------------------------------------------
1 | def validate_path():
2 | import os, sys
3 | os.path.dirname(__file__)
4 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..")
5 | os.chdir(root_dir_assume)
6 | sys.path.append(root_dir_assume)
7 | validate_path() # validate path so you can run from base directory
8 |
9 | from toolbox import get_conf
10 | import requests
11 |
12 | def searxng_request(query, proxies, categories='general', searxng_url=None, engines=None):
13 | url = 'http://localhost:50001/'
14 |
15 | if engines is None:
16 | engine = 'bing,'
17 | if categories == 'general':
18 | params = {
19 | 'q': query, # 搜索查询
20 | 'format': 'json', # 输出格式为JSON
21 | 'language': 'zh', # 搜索语言
22 | 'engines': engine,
23 | }
24 | elif categories == 'science':
25 | params = {
26 | 'q': query, # 搜索查询
27 | 'format': 'json', # 输出格式为JSON
28 | 'language': 'zh', # 搜索语言
29 | 'categories': 'science'
30 | }
31 | else:
32 | raise ValueError('不支持的检索类型')
33 | headers = {
34 | 'Accept-Language': 'zh-CN,zh;q=0.9',
35 | 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36',
36 | 'X-Forwarded-For': '112.112.112.112',
37 | 'X-Real-IP': '112.112.112.112'
38 | }
39 | results = []
40 | response = requests.post(url, params=params, headers=headers, proxies=proxies, timeout=30)
41 | if response.status_code == 200:
42 | json_result = response.json()
43 | for result in json_result['results']:
44 | item = {
45 | "title": result.get("title", ""),
46 | "content": result.get("content", ""),
47 | "link": result["url"],
48 | }
49 | print(result['engines'])
50 | results.append(item)
51 | return results
52 | else:
53 | if response.status_code == 429:
54 | raise ValueError("Searxng（在线搜索服务）当前使用人数太多，请稍后。")
55 | else:
56 | raise ValueError("在线搜索失败，状态码: " + str(response.status_code) + '\t' + response.content.decode('utf-8'))
57 | res = searxng_request("vr environment", None, categories='science', searxng_url=None, engines=None)
58 | print(res)
--------------------------------------------------------------------------------
/tests/test_social_helper.py:
--------------------------------------------------------------------------------
1 | """
2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
3 | """
4 |
5 | import init_test
6 | import os, sys
7 |
8 |
9 | if __name__ == "__main__":
10 | from test_utils import plugin_test
11 | plugin_test(
12 | plugin='crazy_functions.Social_Helper->I人助手',
13 | main_input="""
14 | 添加联系人：
15 | 艾德·史塔克：我的养父，他是临冬城的公爵。
16 | 凯特琳·史塔克：我的养母，她对我态度冷淡，因为我是私生子。
17 | 罗柏·史塔克：我的哥哥，他是北境的继承人。
18 | 艾莉亚·史塔克：我的妹妹，她和我关系亲密，性格独立坚强。
19 | 珊莎·史塔克：我的妹妹，她梦想成为一位淑女。
20 | 布兰·史塔克：我的弟弟，他有预知未来的能力。
21 | 瑞肯·史塔克：我的弟弟，他是个天真无邪的小孩。
22 | 山姆威尔·塔利：我的朋友，他在守夜人军团中与我并肩作战。
23 | 伊格瑞特：我的恋人，她是野人中的一员。
24 | """)
25 |
--------------------------------------------------------------------------------
/tests/test_tts.py:
--------------------------------------------------------------------------------
1 | import edge_tts
2 | import os
3 | import httpx
4 | from toolbox import get_conf
5 |
6 |
7 | async def test_tts():
8 | async with httpx.AsyncClient() as client:
9 | try:
10 | # Forward the request to the target service
11 | import tempfile
12 | import edge_tts
13 | import wave
14 | import uuid
15 | from pydub import AudioSegment
16 | voice = get_conf("EDGE_TTS_VOICE")
17 | tts = edge_tts.Communicate(text="测试", voice=voice)
18 | temp_folder = tempfile.gettempdir()
19 | temp_file_name = str(uuid.uuid4().hex)
20 | temp_file = os.path.join(temp_folder, f'{temp_file_name}.mp3')
21 | await tts.save(temp_file)
22 | try:
23 | mp3_audio = AudioSegment.from_file(temp_file, format="mp3")
24 | mp3_audio.export(temp_file, format="wav")
25 | with open(temp_file, 'rb') as wav_file: t = wav_file.read()
26 | except:
27 | raise RuntimeError("ffmpeg未安装，无法处理EdgeTTS音频。安装方法见`https://github.com/jiaaro/pydub#getting-ffmpeg-set-up`")
28 | except httpx.RequestError as e:
29 | raise RuntimeError(f"请求失败: {e}")
30 |
31 | if __name__ == "__main__":
32 | import asyncio
33 | asyncio.run(test_tts())
--------------------------------------------------------------------------------
/tests/test_utils.py:
--------------------------------------------------------------------------------
1 | from toolbox import get_conf
2 | from toolbox import set_conf
3 | from toolbox import set_multi_conf
4 | from toolbox import get_plugin_handle
5 | from toolbox import get_plugin_default_kwargs
6 | from toolbox import get_chat_handle
7 | from toolbox import get_chat_default_kwargs
8 | from functools import wraps
9 | import sys
10 | import os
11 |
12 |
13 | def chat_to_markdown_str(chat):
14 | result = ""
15 | for i, cc in enumerate(chat):
16 | result += f"\n\n{cc[0]}\n\n{cc[1]}"
17 | if i != len(chat) - 1:
18 | result += "\n\n---"
19 | return result
20 |
21 |
22 | def silence_stdout(func):
23 | @wraps(func)
24 | def wrapper(*args, **kwargs):
25 | _original_stdout = sys.stdout
26 | sys.stdout = open(os.devnull, "w")
27 | sys.stdout.reconfigure(encoding="utf-8")
28 | for q in func(*args, **kwargs):
29 | sys.stdout = _original_stdout
30 | yield q
31 | sys.stdout = open(os.devnull, "w")
32 | sys.stdout.reconfigure(encoding="utf-8")
33 | sys.stdout.close()
34 | sys.stdout = _original_stdout
35 |
36 | return wrapper
37 |
38 |
39 | def silence_stdout_fn(func):
40 | @wraps(func)
41 | def wrapper(*args, **kwargs):
42 | _original_stdout = sys.stdout
43 | sys.stdout = open(os.devnull, "w")
44 | sys.stdout.reconfigure(encoding="utf-8")
45 | result = func(*args, **kwargs)
46 | sys.stdout.close()
47 | sys.stdout = _original_stdout
48 | return result
49 |
50 | return wrapper
51 |
52 |
53 | class VoidTerminal:
54 | def __init__(self) -> None:
55 | pass
56 |
57 |
58 | vt = VoidTerminal()
59 | vt.get_conf = silence_stdout_fn(get_conf)
60 | vt.set_conf = silence_stdout_fn(set_conf)
61 | vt.set_multi_conf = silence_stdout_fn(set_multi_conf)
62 | vt.get_plugin_handle = silence_stdout_fn(get_plugin_handle)
63 | vt.get_plugin_default_kwargs = silence_stdout_fn(get_plugin_default_kwargs)
64 | vt.get_chat_handle = silence_stdout_fn(get_chat_handle)
65 | vt.get_chat_default_kwargs = silence_stdout_fn(get_chat_default_kwargs)
66 | vt.chat_to_markdown_str = chat_to_markdown_str
67 | (
68 | proxies,
69 | WEB_PORT,
70 | LLM_MODEL,
71 | CONCURRENT_COUNT,
72 | AUTHENTICATION,
73 | CHATBOT_HEIGHT,
74 | LAYOUT,
75 | API_KEY,
76 | ) = vt.get_conf(
77 | "proxies",
78 | "WEB_PORT",
79 | "LLM_MODEL",
80 | "CONCURRENT_COUNT",
81 | "AUTHENTICATION",
82 | "CHATBOT_HEIGHT",
83 | "LAYOUT",
84 | "API_KEY",
85 | )
86 |
87 |
88 | def plugin_test(main_input, plugin, advanced_arg=None, debug=True):
89 | from rich.live import Live
90 | from rich.markdown import Markdown
91 |
92 | vt.set_conf(key="API_KEY", value=API_KEY)
93 | vt.set_conf(key="LLM_MODEL", value=LLM_MODEL)
94 |
95 | plugin = vt.get_plugin_handle(plugin)
96 | plugin_kwargs = vt.get_plugin_default_kwargs()
97 | plugin_kwargs["main_input"] = main_input
98 | if advanced_arg is not None:
99 | plugin_kwargs["plugin_kwargs"] = advanced_arg
100 | if debug:
101 | my_working_plugin = (plugin)(**plugin_kwargs)
102 | else:
103 | my_working_plugin = silence_stdout(plugin)(**plugin_kwargs)
104 |
105 | with Live(Markdown(""), auto_refresh=False, vertical_overflow="visible") as live:
106 | for cookies, chat, hist, msg in my_working_plugin:
107 | md_str = vt.chat_to_markdown_str(chat)
108 | md = Markdown(md_str)
109 | live.update(md, refresh=True)
110 |
--------------------------------------------------------------------------------
/tests/test_vector_plugins.py:
--------------------------------------------------------------------------------
1 | """
2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
3 | """
4 |
5 |
6 | import os, sys
7 |
8 |
9 | def validate_path():
10 | dir_name = os.path.dirname(__file__)
11 | root_dir_assume = os.path.abspath(dir_name + "/..")
12 | os.chdir(root_dir_assume)
13 | sys.path.append(root_dir_assume)
14 |
15 |
16 | validate_path() # 返回项目根路径
17 |
18 | if __name__ == "__main__":
19 | from tests.test_utils import plugin_test
20 |
21 | plugin_test(plugin="crazy_functions.知识库问答->知识库文件注入", main_input="./README.md")
22 |
23 | plugin_test(
24 | plugin="crazy_functions.知识库问答->读取知识库作答",
25 | main_input="What is the installation method？",
26 | )
27 |
28 | plugin_test(plugin="crazy_functions.知识库问答->读取知识库作答", main_input="远程云服务器部署？")
29 |
--------------------------------------------------------------------------------
/themes/base64.mjs:
--------------------------------------------------------------------------------
1 | // we have moved mermaid-related code to gradio-fix repository: binary-husky/gradio-fix@32150d0
2 |
--------------------------------------------------------------------------------
/themes/common.py:
--------------------------------------------------------------------------------
1 | from functools import lru_cache
2 | from toolbox import get_conf
3 | CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT")
4 |
5 | def inject_mutex_button_code(js_content):
6 | from crazy_functional import get_multiplex_button_functions
7 | fns = get_multiplex_button_functions()
8 |
9 | template = """
10 | if (multiplex_sel === "{x}") {
11 | let _align_name_in_crazy_function_py = "{y}";
12 | call_plugin_via_name(_align_name_in_crazy_function_py);
13 | return;
14 | }
15 | """
16 |
17 | replacement = ""
18 | for fn in fns.keys():
19 | if fn == "常规对话": continue
20 | replacement += template.replace("{x}", fn).replace("{y}", fns[fn])
21 | js_content = js_content.replace("// REPLACE_EXTENDED_MULTIPLEX_FUNCTIONS_HERE", replacement)
22 | return js_content
23 |
24 | def minimize_js(common_js_path):
25 | try:
26 | import rjsmin, hashlib, glob, os
27 | # clean up old minimized js files, matching `common_js_path + '.min.*'`
28 | for old_min_js in glob.glob(common_js_path + '.min.*.js'):
29 | os.remove(old_min_js)
30 | # use rjsmin to minimize `common_js_path`
31 | c_jsmin = rjsmin.jsmin
32 | with open(common_js_path, "r", encoding='utf-8') as f:
33 | js_content = f.read()
34 | if common_js_path == "themes/common.js":
35 | js_content = inject_mutex_button_code(js_content)
36 | minimized_js_content = c_jsmin(js_content)
37 | # compute sha256 hash of minimized js content
38 | sha_hash = hashlib.sha256(minimized_js_content.encode()).hexdigest()[:8]
39 | minimized_js_path = common_js_path + '.min.' + sha_hash + '.js'
40 | # save to minimized js file
41 | with open(minimized_js_path, "w", encoding='utf-8') as f:
42 | f.write(minimized_js_content)
43 | # return minimized js file path
44 | return minimized_js_path
45 | except:
46 | return common_js_path
47 |
48 | @lru_cache
49 | def get_common_html_javascript_code():
50 | js = "\n"
51 | common_js_path_list = [
52 | "themes/common.js",
53 | "themes/theme.js",
54 | "themes/tts.js",
55 | "themes/init.js",
56 | "themes/welcome.js",
57 | ]
58 |
59 | if ADD_WAIFU: # 添加Live2D
60 | common_js_path_list += [
61 | "themes/waifu_plugin/jquery.min.js",
62 | "themes/waifu_plugin/jquery-ui.min.js",
63 | ]
64 |
65 | for common_js_path in common_js_path_list:
66 | if '.min.' not in common_js_path:
67 | minimized_js_path = minimize_js(common_js_path)
68 | else:
69 | minimized_js_path = common_js_path
70 | jsf = f"file={minimized_js_path}"
71 | js += f"""<script src="{jsf}"></script>\n"""
72 |
73 | if not ADD_WAIFU:
74 | js += """<script>window.loadLive2D = function(){};</script>\n"""
75 |
76 | return js
77 |
--------------------------------------------------------------------------------
/themes/cookies.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/binary-husky/gpt_academic/a7a56b5058fc8e69641e113f615aed8ab3a59a64/themes/cookies.py
--------------------------------------------------------------------------------
/themes/gradios.py:
--------------------------------------------------------------------------------
1 | import os
2 | import gradio as gr
3 | from toolbox import get_conf, ProxyNetworkActivate
4 | from loguru import logger
5 |
6 | CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT")
7 | theme_dir = os.path.dirname(__file__)
8 |
9 |
10 | def dynamic_set_theme(THEME):
11 | set_theme = gr.themes.ThemeClass()
12 | with ProxyNetworkActivate("Download_Gradio_Theme"):
13 | logger.info("正在下载Gradio主题，请稍等。")
14 | try:
15 | if THEME.startswith("Huggingface-"):
16 | THEME = THEME.lstrip("Huggingface-")
17 | if THEME.startswith("huggingface-"):
18 | THEME = THEME.lstrip("huggingface-")
19 | set_theme = set_theme.from_hub(THEME.lower())
20 | except:
21 | logger.error("下载Gradio主题时出现异常。")
22 | return set_theme
23 |
24 |
25 | def adjust_theme():
26 | try:
27 | set_theme = gr.themes.ThemeClass()
28 | with ProxyNetworkActivate("Download_Gradio_Theme"):
29 | logger.info("正在下载Gradio主题，请稍等。")
30 | try:
31 | THEME = get_conf("THEME")
32 | if THEME.startswith("Huggingface-"):
33 | THEME = THEME.lstrip("Huggingface-")
34 | if THEME.startswith("huggingface-"):
35 | THEME = THEME.lstrip("huggingface-")
36 | set_theme = set_theme.from_hub(THEME.lower())
37 | except:
38 | logger.error("下载Gradio主题时出现异常。")
39 |
40 | from themes.common import get_common_html_javascript_code
41 | js = get_common_html_javascript_code()
42 |
43 | if not hasattr(gr, "RawTemplateResponse"):
44 | gr.RawTemplateResponse = gr.routes.templates.TemplateResponse
45 | gradio_original_template_fn = gr.RawTemplateResponse
46 |
47 | def gradio_new_template_fn(*args, **kwargs):
48 | res = gradio_original_template_fn(*args, **kwargs)
49 | res.body = res.body.replace(b"</html>", f"{js}</html>".encode("utf8"))
50 | res.init_headers()
51 | return res
52 |
53 | gr.routes.templates.TemplateResponse = (
54 | gradio_new_template_fn # override gradio template
55 | )
56 | except Exception:
57 | set_theme = None
58 | logger.error("gradio版本较旧, 不能自定义字体和颜色。")
59 | return set_theme
60 |
61 |
62 | with open(os.path.join(theme_dir, "common.css"), "r", encoding="utf-8") as f:
63 | advanced_css = f.read()
64 |
--------------------------------------------------------------------------------
/themes/green.js:
--------------------------------------------------------------------------------
1 |
2 | var academic_chat = null;
3 |
4 | var sliders = null;
5 | var rangeInputs = null;
6 | var numberInputs = null;
7 |
8 | function set_elements() {
9 | academic_chat = document.querySelector('gradio-app');
10 | async function get_sliders() {
11 | sliders = document.querySelectorAll('input[type="range"]');
12 | while (sliders.length == 0) {
13 | await new Promise(r => setTimeout(r, 100));
14 | sliders = document.querySelectorAll('input[type="range"]');
15 | }
16 | setSlider();
17 | }
18 | get_sliders();
19 | }
20 |
21 | function setSlider() {
22 | rangeInputs = document.querySelectorAll('input[type="range"]');
23 | numberInputs = document.querySelectorAll('input[type="number"]')
24 | function setSliderRange() {
25 | var range = document.querySelectorAll('input[type="range"]');
26 | range.forEach(range => {
27 | range.style.backgroundSize = (range.value - range.min) / (range.max - range.min) * 100 + '% 100%';
28 | });
29 | }
30 | setSliderRange();
31 | rangeInputs.forEach(rangeInput => {
32 | rangeInput.addEventListener('input', setSliderRange);
33 | });
34 | numberInputs.forEach(numberInput => {
35 | numberInput.addEventListener('input', setSliderRange);
36 | })
37 | }
38 |
39 | window.addEventListener("DOMContentLoaded", () => {
40 | set_elements();
41 | });
42 |
--------------------------------------------------------------------------------
/themes/gui_advanced_plugin_class.py:
--------------------------------------------------------------------------------
1 | import gradio as gr
2 | import json
3 | from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
4 |
5 | def define_gui_advanced_plugin_class(plugins):
6 | # 定义新一代插件的高级参数区
7 | with gr.Floating(init_x="50%", init_y="50%", visible=False, width="30%", drag="top", elem_id="plugin_arg_menu"):
8 | with gr.Accordion("选择插件参数", open=True, elem_id="plugin_arg_panel"):
9 | for u in range(8):
10 | with gr.Row():
11 | gr.Textbox(show_label=True, label="T1", placeholder="请输入", lines=1, visible=False, elem_id=f"plugin_arg_txt_{u}").style(container=False)
12 | for u in range(8):
13 | with gr.Row(): # PLUGIN_ARG_MENU
14 | gr.Dropdown(label="T1", value="请选择", choices=[], visible=True, elem_id=f"plugin_arg_drop_{u}", interactive=True)
15 |
16 | with gr.Row():
17 | # 这个隐藏textbox负责装入当前弹出插件的属性
18 | gr.Textbox(show_label=False, placeholder="请输入", lines=1, visible=False,
19 | elem_id=f"invisible_current_pop_up_plugin_arg").style(container=False)
20 | usr_confirmed_arg = gr.Textbox(show_label=False, placeholder="请输入", lines=1, visible=False,
21 | elem_id=f"invisible_current_pop_up_plugin_arg_final").style(container=False)
22 |
23 | arg_confirm_btn = gr.Button("确认参数并执行", variant="stop")
24 | arg_confirm_btn.style(size="sm")
25 |
26 | arg_cancel_btn = gr.Button("取消", variant="stop")
27 | arg_cancel_btn.click(None, None, None, _js="""()=>close_current_pop_up_plugin()""")
28 | arg_cancel_btn.style(size="sm")
29 |
30 | arg_confirm_btn.click(None, None, None, _js="""()=>execute_current_pop_up_plugin()""")
31 | invisible_callback_btn_for_plugin_exe = gr.Button(r"未选定任何插件", variant="secondary", visible=False, elem_id="invisible_callback_btn_for_plugin_exe").style(size="sm")
32 | # 随变按钮的回调函数注册
33 | def route_switchy_bt_with_arg(request: gr.Request, input_order, *arg):
34 | arguments = {k:v for k,v in zip(input_order, arg)} # 重新梳理输入参数，转化为kwargs字典
35 | which_plugin = arguments.pop('new_plugin_callback') # 获取需要执行的插件名称
36 | if which_plugin in [r"未选定任何插件"]: return
37 | usr_confirmed_arg = arguments.pop('usr_confirmed_arg') # 获取插件参数
38 | arg_confirm: dict = {}
39 | usr_confirmed_arg_dict = json.loads(usr_confirmed_arg) # 读取插件参数
40 | for arg_name in usr_confirmed_arg_dict:
41 | arg_confirm.update({arg_name: str(usr_confirmed_arg_dict[arg_name]['user_confirmed_value'])})
42 |
43 | if plugins[which_plugin].get("Class", None) is not None: # 获取插件执行函数
44 | plugin_obj = plugins[which_plugin]["Class"]
45 | plugin_exe = plugin_obj.execute
46 | else:
47 | plugin_exe = plugins[which_plugin]["Function"]
48 |
49 | arguments['plugin_advanced_arg'] = arg_confirm # 更新高级参数输入区的参数
50 | if arg_confirm.get('main_input', None) is not None: # 更新主输入区的参数
51 | arguments['txt'] = arg_confirm['main_input']
52 |
53 | # 万事俱备，开始执行
54 | yield from ArgsGeneralWrapper(plugin_exe)(request, *arguments.values())
55 |
56 | return invisible_callback_btn_for_plugin_exe, route_switchy_bt_with_arg, usr_confirmed_arg
57 |
58 |
--------------------------------------------------------------------------------
/themes/svg/arxiv.svg:
--------------------------------------------------------------------------------
1 | <?xml version="1.0"?>
2 | <svg width="1024" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m140,188l584,0l0,164l76,0l0,-208c0,-17.7 -14.3,-32 -32,-32l-672,0c-17.7,0 -32,14.3 -32,32l0,736c0,17.7 14.3,32 32,32l544,0l0,-76l-500,0l0,-648zm274.3,68l-60.6,0c-3.4,0 -6.4,2.2 -7.6,5.4l-127.1,368c-0.3,0.8 -0.4,1.7 -0.4,2.6c0,4.4 3.6,8 8,8l55.1,0c3.4,0 6.4,-2.2 7.6,-5.4l32.7,-94.6l196.2,0l-96.2,-278.6c-1.3,-3.2 -4.3,-5.4 -7.7,-5.4zm12.4,228l-85.5,0l42.8,-123.8l42.7,123.8zm509.3,44l-136,0l0,-93c0,-4.4 -3.6,-8 -8,-8l-56,0c-4.4,0 -8,3.6 -8,8l0,93l-136,0c-13.3,0 -24,10.7 -24,24l0,176c0,13.3 10.7,24 24,24l136,0l0,152c0,4.4 3.6,8 8,8l56,0c4.4,0 8,-3.6 8,-8l0,-152l136,0c13.3,0 24,-10.7 24,-24l0,-176c0,-13.3 -10.7,-24 -24,-24zm-208,152l-88,0l0,-80l88,0l0,80zm160,0l-88,0l0,-80l88,0l0,80z" fill="#00aeff" id="svg_1"/>
6 | </g>
7 | </svg>
--------------------------------------------------------------------------------
/themes/svg/box.svg:
--------------------------------------------------------------------------------
1 | <svg t="1722787038697" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="7850" width="200" height="200"><path d="M902.095238 390.095238l-0.024381 340.041143-0.073143-4.583619A170.666667 170.666667 0 1 0 731.257905 902.095238H195.047619a73.142857 73.142857 0 0 1-73.142857-73.142857V390.095238h780.190476z m-175.542857 219.428572a117.028571 117.028571 0 0 1 101.13219 175.957333l70.217143 70.217143-41.374476 41.374476-70.022095-69.997714A117.028571 117.028571 0 1 1 726.552381 609.52381z m0 73.142857a43.885714 43.885714 0 1 0 0 87.771428 43.885714 43.885714 0 0 0 0-87.771428zM463.238095 438.857143h-195.047619v73.142857h195.047619v-73.142857zM765.123048 121.904762a73.142857 73.142857 0 0 1 65.414095 40.423619l63.829333 127.634286A73.142857 73.142857 0 0 1 901.87581 316.952381H122.831238a73.142857 73.142857 0 0 1 6.339048-20.138667l64.560762-133.607619A73.142857 73.142857 0 0 1 259.584 121.904762h505.539048z" p-id="7851" fill="#1296db"></path></svg>
--------------------------------------------------------------------------------
/themes/svg/brain.svg:
--------------------------------------------------------------------------------
1 | <?xml version="1.0"?>
2 | <svg width="1024" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m832,96a96,96 0 1 1 -90.72,127.52l-1.54,0.26l-3.74,0.22l-256,0l0,256l256,0c1.82,0 3.58,0.16 5.31,0.45a96,96 0 1 1 0,63.07l-1.6,0.26l-3.71,0.22l-256,0l0,256l256,0c1.82,0 3.58,0.16 5.31,0.45a96,96 0 1 1 0,63.07l-1.6,0.26l-3.71,0.22l-288,0a32,32 0 0 1 -31.78,-28.26l-0.22,-3.74l0,-288l-68.03,0a128.06,128.06 0 0 1 -117.57,95.87l-6.4,0.13a128,128 0 1 1 123.97,-160l68.03,0l0,-288a32,32 0 0 1 28.26,-31.78l3.74,-0.22l288,0c1.82,0 3.58,0.16 5.31,0.45a96,96 0 0 1 90.69,-64.45zm0,704a32,32 0 1 0 0,64a32,32 0 0 0 0,-64zm-608,-352a64,64 0 1 0 0,128a64,64 0 0 0 0,-128zm608,32a32,32 0 1 0 0,64a32,32 0 0 0 0,-64zm0,-320a32,32 0 1 0 0,64a32,32 0 0 0 0,-64z" fill="#00aeff" id="svg_1"/>
6 | <path d="m224,384a128,128 0 1 1 0,256a128,128 0 0 1 0,-256zm0,64a64,64 0 1 0 0,128a64,64 0 0 0 0,-128z" fill="#00aeff" id="svg_2"/>
7 | </g>
8 | </svg>
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/themes/svg/check.svg:
--------------------------------------------------------------------------------
1 | <svg t="1722786924074" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="7573" width="200" height="200"><path d="M690.176 146.285714c19.870476 0 38.838857 8.338286 52.345905 22.991238l45.519238 49.420191-280.81981 207.993905-162.694095-101.546667a54.51581 54.51581 0 0 0-75.337143 17.798095c-12.190476 19.748571-10.727619 45.056 3.584 63.268572l182.930286 232.545523a71.046095 71.046095 0 0 0 108.495238 4.022858L870.15619 307.833905l49.493334 53.735619a72.240762 72.240762 0 0 1 0.585143 97.084952L564.931048 854.064762a71.046095 71.046095 0 0 1-105.862096 0L103.789714 458.654476a72.240762 72.240762 0 0 1 0.585143-97.084952l177.078857-192.292572A71.143619 71.143619 0 0 1 333.799619 146.285714h356.376381z m176.420571 73.703619a7.143619 7.143619 0 0 1 9.508572 10.532572L529.261714 610.279619a23.79581 23.79581 0 0 1-36.254476-1.340952l-183.027809-232.643048a7.143619 7.143619 0 0 1 9.386666-10.483809l190.171429 118.686476z" p-id="7574" fill="#1296db"></path></svg>
--------------------------------------------------------------------------------
/themes/svg/conf.svg:
--------------------------------------------------------------------------------
1 | <?xml version="1.0"?>
2 | <svg width="1024" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m373.83,194.49a44.92,44.92 0 1 1 0,-89.84a44.96,44.96 0 1 1 0,89.84m165.43,-163.51l-63.23,0s-189.11,-1.28 -204.17,99.33l0,122.19l241.47,0l0,34.95l-358.3,-0.66s-136.03,9.94 -138.51,206.74l0,57.75s-3.96,190.03 130.12,216.55l92.32,0l0,-128.09a132,132 0 0 1 132.06,-132.03l256.43,0a123.11,123.11 0 0 0 123.18,-123.12l0,-238.62c0,-2.25 -1.19,-103.13 -211.37,-115.02" fill="#00aeff" id="svg_1"/>
6 | <path d="m647.01,853.16c24.84,0 44.96,20.01 44.96,44.85a44.96,44.96 0 1 1 -44.96,-44.85m-165.43,163.51l63.23,0s189.14,1.22 204.17,-99.36l0,-122.22l-241.47,0l0,-34.95l358.27,0.66s136.06,-9.88 138.54,-206.65l0,-57.74s3.96,-190.04 -130.12,-216.56l-92.32,0l0,128.03a132.06,132.06 0 0 1 -132.06,132.1l-256.47,0a123.11,123.11 0 0 0 -123.14,123.08l0,238.59c0,2.24 1.19,103.16 211.37,115.02" fill="#00aeff" id="svg_2"/>
7 | </g>
8 | </svg>
--------------------------------------------------------------------------------
/themes/svg/default.svg:
--------------------------------------------------------------------------------
1 | <svg t="1721122982934" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="1823" width="200" height="200"><path d="M512 512m-512 0a512 512 0 1 0 1024 0 512 512 0 1 0-1024 0Z" fill="#04BEE8" p-id="1824"></path><path d="M324.408781 655.018925C505.290126 655.018925 651.918244 508.387706 651.918244 327.509463c0-152.138029-103.733293-280.047334-244.329811-316.853972C205.813923 52.463528 47.497011 213.017581 8.987325 415.981977 47.587706 553.880127 174.183098 655.018925 324.408781 655.018925z" fill="#FFFFFF" fill-opacity=".2" p-id="1825"></path><path d="M512 1024c282.766631 0 512-229.233369 512-512 0-31.765705-2.891385-62.853911-8.433853-93.018889C928.057169 336.0999 809.874701 285.26268 679.824375 285.26268c-269.711213 0-488.357305 218.645317-488.357305 488.357305 0 54.959576 9.084221 107.802937 25.822474 157.10377C300.626556 989.489417 402.283167 1024 512 1024z" fill="#FFFFFF" fill-opacity=".15" p-id="1826"></path><path d="M732.535958 756.566238c36.389596 0 65.889478-29.499882 65.889477-65.889478 0 36.389596 29.502983 65.889478 65.889478 65.889478-17.053747 0-65.889478 29.502983-65.889478 65.889477 0-36.386495-29.499882-65.889478-65.889477-65.889477zM159.685087 247.279334c25.686819 0 46.51022-20.8234 46.51022-46.51022 0 25.686819 20.8234 46.51022 46.510219 46.51022-12.03607 0-46.51022 20.8234-46.510219 46.510219 0-25.686819-20.8234-46.51022-46.51022-46.510219z" fill="#FFFFFF" fill-opacity=".5" p-id="1827"></path><path d="M206.195307 333.32324c8.562531 0 15.503407-6.940875 15.503406-15.503407 0 8.562531 6.940875 15.503407 15.503407 15.503407-4.012282 0-15.503407 6.940875-15.503407 15.503406 0-8.562531-6.940875-15.503407-15.503406-15.503406z" fill="#FFFFFF" fill-opacity=".3" p-id="1828"></path><path d="M282.161998 248.054504m80.617714 0l299.215746 0q80.617714 0 80.617714 80.617714l0 366.380379q0 80.617714-80.617714 80.617713l-299.215746 0q-80.617714 0-80.617714-80.617713l0-366.380379q0-80.617714 80.617714-80.617714Z" fill="#FFFFFF" p-id="1829"></path><path d="M530.216503 280.611658h113.433774v146.467658c0 10.89967-13.049992 16.498725-20.948978 8.9881l-35.767909-34.009048-35.767909 34.009048C543.266495 443.578041 530.216503 437.978986 530.216503 427.079316V280.611658z" fill="#29C8EB" p-id="1830"></path><path d="M365.105223 280.611658m14.728237 0l0 0q14.728236 0 14.728236 14.728236l0 417.041635q0 14.728236-14.728236 14.728236l0 0q-14.728236 0-14.728237-14.728236l0-417.041635q0-14.728236 14.728237-14.728236Z" fill="#29C8EB" p-id="1831"></path></svg>
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/themes/svg/doc.svg:
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1 | <?xml version="1.0"?>
2 | <svg width="1024" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m298.67,96a32,32 0 0 1 0,64a138.67,138.67 0 0 0 -138.67,138.67l0,42.66a32,32 0 0 1 -64,0l0,-42.66a202.67,202.67 0 0 1 202.67,-202.67zm597.33,554.67a32,32 0 0 1 32,32l0,42.66a202.67,202.67 0 0 1 -202.67,202.67l-42.66,0a32,32 0 0 1 0,-64l42.66,0a138.67,138.67 0 0 0 138.67,-138.67l0,-42.66a32,32 0 0 1 32,-32zm-128,-405.34a32,32 0 0 1 0,64l-213.33,0a32,32 0 0 1 0,-64l213.33,0zm0,128a32,32 0 0 1 0,64l-128,0a32,32 0 0 1 0,-64l128,0z" fill="#00aeff" id="svg_1"/>
6 | <path d="m780.8,96a138.67,138.67 0 0 1 138.67,138.67l0,213.33a138.67,138.67 0 0 1 -138.67,138.67l-98.13,0a32,32 0 0 1 0,-64l98.13,0a74.67,74.67 0 0 0 74.67,-74.67l0,-213.33a74.67,74.67 0 0 0 -74.67,-74.67l-247.47,0a74.67,74.67 0 0 0 -74.66,74.67l0,106.66a32,32 0 0 1 -64,0l0,-106.66a138.67,138.67 0 0 1 138.66,-138.67l247.47,0zm-487.68,500.05a32,32 0 0 1 45.23,0l64,64a32,32 0 0 1 0,45.23l-64,64a32,32 0 0 1 -45.23,-45.23l41.34,-41.38l-41.38,-41.39a32,32 0 0 1 -3.07,-41.64l3.11,-3.59z" fill="#00aeff" id="svg_2"/>
7 | <path d="m448,437.33a138.67,138.67 0 0 1 138.67,138.67l0,213.33a138.67,138.67 0 0 1 -138.67,138.67l-213.33,0a138.67,138.67 0 0 1 -138.67,-138.67l0,-213.33a138.67,138.67 0 0 1 138.67,-138.67l213.33,0zm0,64l-213.33,0a74.67,74.67 0 0 0 -74.67,74.67l0,213.33c0,41.22 33.45,74.67 74.67,74.67l213.33,0a74.67,74.67 0 0 0 74.67,-74.67l0,-213.33a74.67,74.67 0 0 0 -74.67,-74.67z" fill="#00aeff" id="svg_3"/>
8 | </g>
9 | </svg>
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/themes/svg/img.svg:
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1 | <?xml version="1.0"?>
2 | <svg width="1024" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m960,234l0,556c0,5.52 -4.48,10 -10,10l-438,0l0,-576l438,0c5.52,0 10,4.48 10,10z" fill="#F7FEFE" id="svg_1"/>
6 | <path d="m931.93,800l-419.93,0l0,-202.03l114.19,-114.19c5.21,-5.21 13.71,-5 18.66,0.44l287.08,315.78z" fill="#3404FC" id="svg_2"/>
7 | <path d="m512,800l256,0l-256,-275.69l0,275.69z" fill="#0097FF" id="svg_3"/>
8 | <path d="m848,336m-48,0a48,48 0 1 0 96,0a48,48 0 1 0 -96,0z" fill="#EC1C36" id="svg_4"/>
9 | <path d="m305.29,242.44m-32,0a32,32 0 1 0 64,0a32,32 0 1 0 -64,0z" fill="#00aeff" id="svg_5"/>
10 | <path d="m112,320m-32,0a32,32 0 1 0 64,0a32,32 0 1 0 -64,0z" fill="#00aeff" id="svg_6"/>
11 | <path d="m96,512m-32,0a32,32 0 1 0 64,0a32,32 0 1 0 -64,0z" fill="#00aeff" id="svg_7"/>
12 | <path d="m305.29,781.56m-32,0a32,32 0 1 0 64,0a32,32 0 1 0 -64,0z" fill="#00aeff" id="svg_8"/>
13 | <path d="m112,704m-32,0a32,32 0 1 0 64,0a32,32 0 1 0 -64,0z" fill="#00aeff" id="svg_9"/>
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16 | </svg>
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1 | <?xml version="1.0"?>
2 | <svg width="1066" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m443.9,511.45a96,96 0 1 0 192,0a96,96 0 0 0 -192,0zm96,32a32,32 0 1 1 0,-64a32,32 0 0 1 0,64z" fill="#00aeff" id="svg_1"/>
6 | <path d="m74.67,512c0,80.17 65.87,142.08 147.54,181.67c84.26,40.84 198.06,65.07 321.7,65.07c123.74,0 237.49,-24.23 321.75,-65.07c81.71,-39.63 147.59,-101.54 147.59,-181.71c0,-80.22 -65.88,-142.08 -147.59,-181.68c-84.26,-40.87 -198.05,-65.11 -321.7,-65.11c-123.69,0 -237.49,24.24 -321.71,65.11c-81.71,39.6 -147.58,101.51 -147.58,181.68l0,0.04zm469.29,172.07c-114.9,0 -217.09,-22.61 -289.15,-57.6c-74.67,-36.18 -105.48,-79.01 -105.48,-114.47c0,-35.46 30.85,-78.29 105.48,-114.52c72.06,-34.94 174.25,-57.6 289.15,-57.6c114.9,0 217.09,22.66 289.15,57.6c74.67,36.23 105.47,79.06 105.47,114.52c0,35.5 -30.85,78.34 -105.47,114.52c-72.11,34.98 -174.25,57.6 -289.15,57.6l0,-0.05z" fill="#00aeff" id="svg_2"/>
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9 | </g>
10 | </svg>
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1 | <?xml version="1.0"?>
2 | <svg width="1024" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m671.27,337.36l2.05,1.92a174.18,174.18 0 0 1 0.19,244.18l-383.3,390.22a168.04,168.04 0 0 1 -237.73,1.79l-2.04,-2.05a174.18,174.18 0 0 1 -0.26,-244.12l383.3,-390.15a168.04,168.04 0 0 1 237.73,-1.79l0.06,0zm-165.09,73.2l-383.31,390.22a72.31,72.31 0 0 0 0.07,101.36l0.77,0.83a66.29,66.29 0 0 0 93.87,-0.7l383.3,-390.22a72.31,72.31 0 0 0 0,-101.42l-0.83,-0.77a66.36,66.36 0 0 0 -93.87,0.7zm282.32,209.7a47.35,47.35 0 0 1 0.64,0.45l122.48,72.05c23.04,13.57 30.91,43.07 17.79,66.29a47.35,47.35 0 0 1 -64.63,17.92l-0.58,-0.45l-122.48,-72.05a48.95,48.95 0 0 1 -17.78,-66.29a47.35,47.35 0 0 1 64.63,-17.92l-0.07,0zm187.43,-191.84a48.38,48.38 0 0 1 0,96.69l-140.52,0a48.38,48.38 0 0 1 0,-96.69l140.52,0zm-49.27,-292.63l0.64,0.64a48.82,48.82 0 0 1 0,68.4l-100.66,102.58a46.97,46.97 0 0 1 -66.42,0.64l-0.64,-0.64a48.82,48.82 0 0 1 0,-68.41l100.66,-102.57a46.97,46.97 0 0 1 66.42,-0.64zm-632.55,-35.64a46.97,46.97 0 0 1 0.58,0.63l100.65,102.52a48.82,48.82 0 0 1 0,68.47a46.97,46.97 0 0 1 -66.42,0.64l-0.64,-0.64l-100.65,-102.58a48.82,48.82 0 0 1 0,-68.47a46.97,46.97 0 0 1 66.48,-0.57zm284.57,-100.15c26.23,0 47.48,21.24 47.48,47.48l0,146.92a47.42,47.42 0 1 1 -94.9,0l0,-146.92c0,-26.24 21.31,-47.48 47.42,-47.48z" fill="#00aeff" id="svg_1"/>
6 | </g>
7 | </svg>
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1 | <?xml version="1.0"?>
2 | <svg width="1092" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m1010.55,424.93c0,86.01 -65.36,155.88 -147.04,166.63l-43.63,0c-81.68,-10.75 -147.04,-80.62 -147.04,-166.63l-92.57,0c0,123.63 92.6,231.11 212.41,252.62l0,107.52l87.17,0l0,-107.52c119.81,-21.51 212.42,-123.63 212.42,-252.59l-81.72,0l0,-0.03zm-76.25,-231.16c0,-53.76 -43.56,-91.37 -92.57,-91.37a91.2,91.2 0 0 0 -92.61,91.37l0,91.38l190.64,0l0,-91.38l-5.46,0zm-190.64,231.16c0,53.76 43.59,91.37 92.61,91.37a91.2,91.2 0 0 0 92.6,-91.37l0,-91.38l-185.21,0l0,91.38zm-279.45,-274.23l-139.94,-140.46l-6.83,-6.83l-3.41,-3.41l-3.42,3.41l-6.82,6.86l-20.48,20.55l-3.42,3.42l3.42,6.86l13.65,13.68l75.09,75.37l-153.6,0c-122.88,6.83 -218.45,109.57 -218.45,229.44l0,10.28l51.2,0l0,-10.24c0,-92.5 75.09,-171.28 167.25,-178.11l153.6,0l-75.09,75.33l-10.24,10.28l-3.41,6.82l-3.42,3.45l3.42,3.41l27.3,27.41l3.42,3.42l3.41,-3.42l30.72,-30.82l116.05,-116.43l3.42,-3.41l-3.42,-6.86zm-406.18,383.55l0,130.16l64.85,0l0,-65.06l129.71,0l0,359.59l-64.86,0l0,65.06l194.56,0l0,-65.06l-64.85,0l0,-359.59l129.71,0l0,65.06l64.85,0l0,-130.16l-453.97,0z" fill="#00aeff" id="svg_1"/>
6 | </g>
7 | </svg>
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1 | <?xml version="1.0"?>
2 | <svg width="1024" height="1024" xmlns="http://www.w3.org/2000/svg" xmlns:svg="http://www.w3.org/2000/svg" class="icon" version="1.1">
3 | <g class="layer">
4 | <title>Layer 1</title>
5 | <path d="m256,64a192,192 0 0 0 -192,192l0,512a192,192 0 0 0 192,192l512,0a192,192 0 0 0 192,-192l0,-512a192,192 0 0 0 -192,-192l-512,0zm92.16,416l-158.08,-158.08l67.84,-67.9l169.41,169.34a80,80 0 0 1 0,113.15l-169.41,169.35l-67.84,-67.78l158.08,-158.08zm131.84,160l288,0l0,96l-288,0l0,-96z" fill="#00aeff" id="svg_1"/>
6 | <path d="m190.08,638.02l158.08,-158.08l-158.08,-158.08l67.84,-67.84l169.41,169.34a80,80 0 0 1 0,113.15l-169.41,169.35l-67.84,-67.78l0,-0.06zm577.92,1.92l-288,0l0,96l288,0l0,-95.94l0,-0.06z" fill="#2951E0" id="svg_2" opacity="0.2"/>
7 | </g>
8 | </svg>
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/themes/theme.js:
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1 | async function try_load_previous_theme(){
2 | if (getCookie("js_theme_selection_cookie")) {
3 | theme_selection = getCookie("js_theme_selection_cookie");
4 | let css = localStorage.getItem('theme-' + theme_selection);
5 | if (css) {
6 | change_theme(theme_selection, css);
7 | }
8 | }
9 | }
10 |
11 | async function change_theme(theme_selection, css) {
12 | if (theme_selection.length==0) {
13 | try_load_previous_theme();
14 | return;
15 | }
16 |
17 | var existingStyles = document.querySelectorAll("body > gradio-app > div > style")
18 | for (var i = 0; i < existingStyles.length; i++) {
19 | var style = existingStyles[i];
20 | style.parentNode.removeChild(style);
21 | }
22 | var existingStyles = document.querySelectorAll("style[data-loaded-css]");
23 | for (var i = 0; i < existingStyles.length; i++) {
24 | var style = existingStyles[i];
25 | style.parentNode.removeChild(style);
26 | }
27 |
28 | setCookie("js_theme_selection_cookie", theme_selection, 3);
29 | localStorage.setItem('theme-' + theme_selection, css);
30 |
31 | var styleElement = document.createElement('style');
32 | styleElement.setAttribute('data-loaded-css', 'placeholder');
33 | styleElement.innerHTML = css;
34 | document.body.appendChild(styleElement);
35 | }
36 |
37 |
38 | // // 记录本次的主题切换
39 | // async function change_theme_prepare(theme_selection, secret_css) {
40 | // setCookie("js_theme_selection_cookie", theme_selection, 3);
41 | // }
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/themes/waifu_plugin/source:
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1 | https://github.com/fghrsh/live2d_demo
2 |
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/version:
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1 | {
2 | "version": 3.93,
3 | "show_feature": true,
4 | "new_feature": "支持deepseek-reason(r1) <-> 字体和字体大小自定义 <-> 优化前端并修复TTS的BUG <-> 添加时间线回溯功能 <-> 支持chatgpt-4o-latest <-> 增加RAG组件 <-> 升级多合一主提交键"
5 | }
6 |
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